Pipeline run
56e5af59-6725-46eb-a8e8-9cfc32e098f4
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Pega Developer
CASE Fslug: pega-developer · id: 24 · source: db
The primary skills align closely with the Pega Developer role, particularly with SQL and other related technologies.
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
A technology services client of ours is looking for multiple APM_GE Support Analysts to join them on a Contract basis. Job Title : APM_GE Support Analyst Experience Needed: 5 - 8 years Location: Mumbai/Pune/Chennai/Bangalore/Hyderabad/Delhi/Noida/Kolkata, Notice Period: Immediate Joiners Required Skills: APM 4.3 version to APM 5 Version, SSRS reports,TMLs APM connect Payroll: Swift Staffing solutions Client: LTIMindtree JR Number : 1259182 Role Description: Experience in APM_GE Support Analyst for APM 4.3 version. • Should have experience on APM_GE Upgradation from APM 4.3 version to APM 5 Version or latest. • Designing and execution of policy in the Meridium and analyzing Instance validation and execution. • Running Bulk analysis on the TMLs on frequent basis. • Designing of SSRS reports and deploying them into APM. • Good knowledge of Data load interface enabling bulk data load from Maximo to Meridium by syncing Functional locations, equipment. Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any. • Also working on health indicators and PI Tags. • Good understanding of APM Connect Administration center. • Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend. • Onboarding new users into APM and giving proper privileges and assigning relevant roles and groups. • Configuration and troubleshooting Meridium instances with various modules. • Interacting with the business users, collecting requirements, and providing solutions. • Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide. • Taking care of the support activities and raising the tickets for the same in client ticketing tool. • Raising change requests and implementing change in the application. • Experience on enhancement tasks to make the Customization and Development. • Experience on policy designer Creating SQL queries based on client request and for SSRS report Feel free to reach out to safa.m@s3staff.com for any additional information.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Aliases — catalog
- SQL (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Query Language
- Vendor
- ANSI
- License
- unknown
- Year introduced
- 1974
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 97
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Pega Programming Languages & DSLs Catalog dimension db id 267
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Reporting Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Asset Management Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Asset Management Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Application Performance Monitoring
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Application Performance Monitoring
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Testing Processes
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| SQL | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| SQL | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | SSRS | type=Reporting Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Maximo | type=Asset Management Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Meridium | type=Asset Management Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | APM | type=Application Performance Monitoring subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | APM Connect Administration Center | type=Application Performance Monitoring subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | UAT | type=Testing Processes subtype=general nature=PRACTICE lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"archetype_override_applied": true,
"archetype_override_matched_skills": [
"Swift",
"Make",
"Role",
"SQL",
"Location",
"roles"
],
"certifications": [],
"company_name": "LTIMindtree",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": 8,
"min": 5,
"raw": "5 - 8 years"
},
"job_locations": [
{
"aliases": [
"Bombay"
],
"city": "Mumbai",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Pune",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [
"Madras"
],
"city": "Chennai",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": "Karnataka",
"work_mode": null
},
{
"aliases": [],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Delhi",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Noida",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [
"Calcutta"
],
"city": "Kolkata",
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "APM_GE Support Analyst",
"role_aliases": [
"Support Analyst",
"APM Support Analyst"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 15,
"heading": "Role Description",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Experience in APM_GE Support Analyst",
"last_5_words": "and for SSRS report"
},
"text": "Experience in APM_GE Support Analyst for APM 4.3 version.\n\u2022 Should have experience on APM_GE Upgradation from APM 4.3 version to APM 5 Version or latest.\n\u2022 Designing and execution of policy in the Meridium and analyzing Instance validation and execution.\n\u2022 Running Bulk analysis on the TMLs on frequent basis.\n\u2022 Designing of SSRS reports and deploying them into APM.\n\u2022 Good knowledge of Data load interface enabling bulk data load from Maximo to Meridium by syncing Functional locations, equipment. Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any.\n\u2022 Also working on health indicators and PI Tags.\n\u2022 Good understanding of APM Connect Administration center.\n\u2022 Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend.\n\u2022 Onboarding new users into APM and giving proper privileges and assigning relevant roles and groups.\n\u2022 Configuration and troubleshooting Meridium instances with various modules.\n\u2022 Interacting with the business users, collecting requirements, and providing solutions.\n\u2022 Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.\n\u2022 Taking care of the support activities and raising the tickets for the same in client ticketing tool.\n\u2022 Raising change requests and implementing change in the application.\n\u2022 Experience on enhancement tasks to make the Customization and Development.\n\u2022 Experience on policy designer Creating SQL queries based on client request and for SSRS report",
"word_count": 309
}
],
"urls": [
{
"type": "other",
"url": "mailto:safa.m@s3staff.com"
}
]
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "SQL"
},
{
"is_primary": true,
"skill_name": "SSRS"
},
{
"is_primary": true,
"skill_name": "Maximo"
},
{
"is_primary": true,
"skill_name": "Meridium"
},
{
"is_primary": true,
"skill_name": "APM"
},
{
"is_primary": true,
"skill_name": "APM Connect Administration Center"
},
{
"is_primary": true,
"skill_name": "UAT"
}
],
"jd_role": {
"display_name": "APM_GE Support Analyst",
"rationale": null,
"role_aliases": [
"Support Analyst",
"APM Support Analyst"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"archetype_override_applied": true,
"archetype_override_matched_skills": [
"Swift",
"Make",
"Role",
"SQL",
"Location",
"roles"
],
"certifications": [],
"company_name": "LTIMindtree",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": 8,
"min": 5,
"raw": "5 - 8 years"
},
"job_locations": [
{
"aliases": [
"Bombay"
],
"city": "Mumbai",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Pune",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [
"Madras"
],
"city": "Chennai",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": "Karnataka",
"work_mode": null
},
{
"aliases": [],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Delhi",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Noida",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [
"Calcutta"
],
"city": "Kolkata",
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "APM_GE Support Analyst",
"role_aliases": [
"Support Analyst",
"APM Support Analyst"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 15,
"heading": "Role Description",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Experience in APM_GE Support Analyst",
"last_5_words": "and for SSRS report"
},
"text": "Experience in APM_GE Support Analyst for APM 4.3 version.\n\u2022 Should have experience on APM_GE Upgradation from APM 4.3 version to APM 5 Version or latest.\n\u2022 Designing and execution of policy in the Meridium and analyzing Instance validation and execution.\n\u2022 Running Bulk analysis on the TMLs on frequent basis.\n\u2022 Designing of SSRS reports and deploying them into APM.\n\u2022 Good knowledge of Data load interface enabling bulk data load from Maximo to Meridium by syncing Functional locations, equipment. Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any.\n\u2022 Also working on health indicators and PI Tags.\n\u2022 Good understanding of APM Connect Administration center.\n\u2022 Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend.\n\u2022 Onboarding new users into APM and giving proper privileges and assigning relevant roles and groups.\n\u2022 Configuration and troubleshooting Meridium instances with various modules.\n\u2022 Interacting with the business users, collecting requirements, and providing solutions.\n\u2022 Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.\n\u2022 Taking care of the support activities and raising the tickets for the same in client ticketing tool.\n\u2022 Raising change requests and implementing change in the application.\n\u2022 Experience on enhancement tasks to make the Customization and Development.\n\u2022 Experience on policy designer Creating SQL queries based on client request and for SSRS report",
"word_count": 309
}
],
"urls": [
{
"type": "other",
"url": "mailto:safa.m@s3staff.com"
}
]
},
"rejected": false,
"rejection_reason": null,
"run_id": "56e5af59-6725-46eb-a8e8-9cfc32e098f4",
"stage3_signals": {
"alias_found": false,
"alias_match_roles": [],
"kra_match_roles": [
{
"display_name": "Fullstack Developer",
"kra_matches": [
{
"kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
"sentence": "Interacting with the business users, collecting requirements, and providing solutions.",
"similarity": 0.5618
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend.",
"similarity": 0.5084
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Experience on policy designer Creating SQL queries based on client request and for SSRS report",
"similarity": 0.4295
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.4999,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Interacting with the business users, collecting requirements, and providing solutions.",
"similarity": 0.5204
},
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend.",
"similarity": 0.4932
},
{
"kra_text": "Monitors pipeline health, SLA breach alerts, and job failure notifications, and performs root cause analysis for data pipeline incidents.",
"sentence": "Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any.",
"similarity": 0.4573
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.4903,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Drupal Dev",
"kra_matches": [
{
"kra_text": "module customization and maintenance",
"sentence": "Experience on enhancement tasks to make the Customization and Development.",
"similarity": 0.5552
},
{
"kra_text": "module customization and maintenance",
"sentence": "Configuration and troubleshooting Meridium instances with various modules.",
"similarity": 0.4544
},
{
"kra_text": "site troubleshooting and defect fixes",
"sentence": "Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.",
"similarity": 0.4433
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 228,
"score": 0.4843,
"slug": "drupal-dev",
"total_count": null
},
{
"display_name": "MLOps Engineer",
"kra_matches": [
{
"kra_text": "Validates model performance benchmarks, data schema contracts, and system integration health before signing off on production release readiness.",
"sentence": "Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.",
"similarity": 0.4715
},
{
"kra_text": "Supports ML platform incidents by diagnosing model serving failures, feature store pipeline breaks, and training environment configuration issues.",
"sentence": "Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any.",
"similarity": 0.4574
},
{
"kra_text": "Coordinates model promotion workflows across development, staging, and production environments including integration testing and data contract validation.",
"sentence": "Experience on enhancement tasks to make the Customization and Development.",
"similarity": 0.4556
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 16,
"score": 0.4615,
"slug": "ml-ops-engineer",
"total_count": null
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": [
{
"kra_text": "Reviews and enforces access control policies, privilege escalation procedures, role-based access control, and identity governance workflows.",
"sentence": "Onboarding new users into APM and giving proper privileges and assigning relevant roles and groups.",
"similarity": 0.4879
},
{
"kra_text": "Designs and implements security controls including SIEM integration, endpoint detection and response, identity management, and firewall rule management.",
"sentence": "Designing and execution of policy in the Meridium and analyzing Instance validation and execution.",
"similarity": 0.4614
},
{
"kra_text": "Conducts security posture assessments, vulnerability scans, and penetration testing to identify weaknesses and evaluate overall system security.",
"sentence": "Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.",
"similarity": 0.434
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 5,
"score": 0.4611,
"slug": "cybersecurity-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"SQL"
],
"role_id": 2,
"score": 0.1429,
"slug": "data-engineer",
"total_count": 7
},
{
"display_name": "Pega Developer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"SQL"
],
"role_id": 24,
"score": 0.1429,
"slug": "pega-developer",
"total_count": 7
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "F",
"chosen_role": null,
"confidence": 0.65,
"is_new_role": false,
"llm2_fired": true,
"llm2_reasoning": "The JD\u2019s focus on SQL-based data integration, ETL processes, SSRS reporting and data analysis aligns closely with a Data Engineer role.",
"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": true,
"reasoning": "LLM2 unsure (confidence 0.65 \u003c 0.7); queueing",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": null,
"centroid_updated": false,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [],
"queue_entry_id": 58,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 271,
"existing_alias_text": "SQL",
"input_term": "SQL",
"matched_canonical": {
"category_id": 6,
"display_name": "SQL",
"id": 101,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "sql",
"sub_category_id": 97,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"chosen_role": {
"display_name": "Pega Developer",
"id": 24,
"rationale": "The primary skills align closely with the Pega Developer role, particularly with SQL and other related technologies.",
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_final_skills": [
"SQL",
"SSRS",
"Maximo",
"Meridium",
"APM",
"APM Connect Administration Center",
"UAT"
],
"input_llm_skills": [
"SQL",
"SSRS",
"Maximo",
"Meridium",
"APM",
"APM Connect Administration Center",
"UAT"
],
"new_aliases_persisted": 0,
"run_id": "56e5af59-6725-46eb-a8e8-9cfc32e098f4",
"skills_detail": [
{
"aliases_in_db": [
{
"alias_text": "SQL",
"alias_type": "CANONICAL",
"id": 271,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "SQL",
"id": 101,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "sql",
"sub_category_id": 97,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "SQL",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "SSRS",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Reporting Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "ssrs",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Maximo",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Asset Management Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "maximo",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Meridium",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Asset Management Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "meridium",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "APM",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Application Performance Monitoring",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "apm",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "APM Connect Administration Center",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Application Performance Monitoring",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "apm-connect-administration-center",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "UAT",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Testing Processes",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "uat",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"SSRS",
"Maximo",
"Meridium",
"APM",
"APM Connect Administration Center",
"UAT"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Pega Developer",
"id": 24,
"rationale": "The primary skills align closely with the Pega Developer role, particularly with SQL and other related technologies.",
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "SQL",
"tag": "in_db"
},
{
"skill": "SSRS",
"tag": "new"
},
{
"skill": "Maximo",
"tag": "new"
},
{
"skill": "Meridium",
"tag": "new"
},
{
"skill": "APM",
"tag": "new"
},
{
"skill": "APM Connect Administration Center",
"tag": "new"
},
{
"skill": "UAT",
"tag": "new"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 24,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"dimension_id": 267,
"input_skill": "SQL",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 101,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 24,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "SQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 101,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 0
},
"planner_output": null,
"run_id": "56e5af59-6725-46eb-a8e8-9cfc32e098f4"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.