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AIWorkhub

AIWorkhub

by shrec
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

aiworkhub_manager_skill_retirement_report

Read-only

Reports each skill's injectability, evidence-anchor cards, and adjudicated outcome, flagging when injection-rate denominators are missing so managers can review retirement recommendations without writes.

Instructions

MANAGER READ: measure every stored skill against its own failure class.

Reports, per skill, whether it is injectable at all, the cards its evidence anchors to, and the adjudicated outcome of those cards. It also reports whether the injection denominator exists in this repository -- and when it does not, says so with both counts instead of computing a rate against a zero denominator. Verdicts are recommendations; retirement stays manager-gated and this never writes.

Summary mode (default) folds each skill's evidence_anchors list to {count, sha256} (digest of its canonical JSON); full=true returns the anchor-card lists unchanged.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "aiworkhub_manager_skill_retirement_report"
  }
}

Input Schema

NameRequiredDescriptionDefault
fullNoTrue returns each skill's complete evidence_anchors card list; default false folds it to a count and sha256.
min_anchorsNoMinimum resolvable evidence-anchor cards a skill needs before it can get a verdict other than insufficient_evidence; default 3.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.12.67
    • addedInput schema / properties / full / description
      Added value: +"True returns each skill's complete evidence_anchors card list; default false folds it to a count and sha256."
    • addedInput schema / properties / min_anchors / description
      Added value: +"Minimum resolvable evidence-anchor cards a skill needs before it can get a verdict other than insufficient_evidence; default 3."
  2. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Read-only and closed-world are already declared by annotations, but the description earns credit for adding that retiring is manager-gated, that this never writes, and that a missing injection denominator is reported as raw counts rather than a rate against zero. That zero-denominator handling is exactly the behavioral edge case an agent needs and the annotations cannot express.

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?

The 'MANAGER READ' label and the core purpose are front-loaded, and the mode-folding paragraph is genuinely load-bearing. The middle section about the denominator is dense but each sentence carries distinct information.

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

Completeness4/5

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

An output schema exists, so return shapes need not be restated, and the description still covers scope, mode behavior, and non-write semantics. What remains unstated is how to interpret a verdict or what the failure classes are, which an agent using the report would want.

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 100%, so the baseline is 3, but the description explains the effect of 'full' semantically: summary mode folds evidence_anchors to {count, sha256} of canonical JSON while full=true returns the lists unchanged. Only min_anchors is left to the schema, which documents it adequately.

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

Purpose4/5

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

States a specific verb and resource: it measures every stored skill against its failure class and reports injectability, evidence anchors, and adjudicated card outcomes. That is far more specific than the sibling skill_* tools, but it never names an alternative to differentiate itself from skill_usage or skill_evidence_sweep.

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

Usage Guidelines3/5

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

The 'MANAGER READ' prefix and 'verdicts are recommendations; retirement stays manager-gated' establish the decision context in which to use it, and the default-vs-full mode guidance is explicit. Yet it never says when to choose this over nearby tools such as skill_evidence_sweep or dashboard_skills, so the routing is only implied.

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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