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Personalised AI augmentation system — makes you better at your work, not dependent on AI

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Status
Unhealthy
OAuth
Works in Glama
Last Tested
Transport
Streamable HTTP
URL
Repository
angelo-leone/talent-augmenting-layer
GitHub Stars
0

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool update
    • Changedtalent_assess_start1 field changed
      • changedInput schema / properties / name / description
        Previous value: -"Name of the person being assessed (optional — can be collected during the assessment)"New value: +"Name of the person being assessed (optional: can be collected during the assessment)"
  2. 15 tool updates
    • First observedtalent_assess_create_profile
    • First observedtalent_assess_score
    • First observedtalent_assess_start
    • First observedtalent_classify_task
    • First observedtalent_delete_profile
    • First observedtalent_get_calibration
    • First observedtalent_get_profile
    • First observedtalent_get_progression
    • First observedtalent_list_profiles
    • First observedtalent_log_interaction
    • First observedtalent_org_summary
    • First observedtalent_parse_telemetry
    • First observedtalent_save_profile
    • First observedtalent_status
    • First observedtalent_suggest_domains

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TDQS

A4/5.0
Disambiguation4/5

Most tools have distinct purposes, but some overlap exists. For example, talent_get_profile and talent_status both provide user overviews, though status includes progression and warnings. talent_assess_create_profile and talent_save_profile both handle profile saving, but create_profile is specifically for assessment-generated profiles while save_profile is for general updates. The descriptions clarify these distinctions, preventing major confusion.

Naming Consistency5/5

Tool names follow a highly consistent snake_case pattern with a clear 'talent_' prefix and descriptive verb_noun combinations. Examples include talent_assess_start, talent_get_profile, and talent_log_interaction. This uniformity makes the tool set predictable and easy to navigate, with no deviations in naming style.

Tool Count5/5

With 15 tools, the count is well-suited for the server's purpose of talent assessment and management. It covers the full lifecycle from assessment (start, score, create_profile) to ongoing management (get_profile, log_interaction, get_progression) and organizational oversight (org_summary). Each tool appears necessary, with no obvious bloat or missing core functions.

Completeness5/5

The tool set provides comprehensive coverage for talent assessment and augmentation. It includes assessment initiation and scoring, profile CRUD operations (create, get, save, delete, list), interaction logging and telemetry parsing, progression tracking, calibration management, task classification, and organizational summaries. No significant gaps are evident; agents can handle end-to-end workflows without dead ends.