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Maestro Career Studio

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by seinun-ai
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Python
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Retire Career Points

kb_retire_points
Idempotent

Batch-retire career knowledge base points so they stop being offered to resumes and the career export; existing resume text stays and points can be restored later.

Instructions

Batch-retire Career KB points: they stop being offered to resumes and the career export; resumes that already use them keep their text. Reversible from /career (Use again). The state written is the user's decision about the listed points; the server does not check that the user reviewed them (a convention, not enforcement, the same gate as kb_approve_points).

1-500 ids; repeats collapse to one result row. Per-id results are honest:
unknown ids return ok=false detail="not found" and the rest still proceed.
Response is {results: [{id, ok, state, detail}], next}; next is a hint
(null when suppressed or unavailable).

Input Schema

NameRequiredDescriptionDefault
point_idsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.12.0

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the annotations: discloses that existing resumes keep their text, that the action is reversible from a specific UI location, and that review is not server-enforced. Per-id outcome semantics (unknown ids return ok=false detail="not found" and the rest still proceed) are exactly the kind of behavior an agent needs before mutating state, and the idempotent hint is consistent with "repeats collapse to one result row."

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the effect and reversibility, then moves to limits and response shape. Dense but every clause carries information; the nested parenthetical ("a convention, not enforcement, the same gate as kb_approve_points") is slightly awkward but earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A single-parameter mutation tool with no output schema, yet the description covers the state change, reversibility, batching limits, per-id error behavior, and the response envelope including the `next` field. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% for the single `point_ids` array, but the description compensates with cardinality bounds (1-500), de-duplication semantics, and per-id failure behavior. It stops short of describing the id format or where ids come from (presumably kb_list_points).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Batch-retire Career KB points") plus the exact effect (no longer offered to resumes and the career export, while existing resume text is preserved). This clearly separates it from siblings like kb_list_points, kb_edit_point, and kb_approve_points.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear operating context: reversibility via /career "Use again" and the fact that the server treats review as a convention rather than enforcement, mirroring kb_approve_points. It does not, however, explicitly say when to choose this over an alternative (e.g., deleting vs retiring a point).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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