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AIWorkhub

AIWorkhub

by shrec
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

aiworkhub_task_usage_report

Read-only

Generate a task usage report filtered by topic, runner, or status, with a bounded summary by default and full raw details when requested.

Instructions

Return task usage report, optionally filtered.

full=True returns the core usage-report payload exactly as before. The default keeps every other top-level key verbatim (schema_id, record_count, *_observed_records, *_unknown_records, ...) and replaces stdout with a bounded summary: a header line, one line per runner (records, observed total_tokens sum, observed cost_usd sum, usage-unknown count) and then the top 20 records by observed total_tokens in the existing pipe format, beside detail_omitted (fingerprint of the full stdout) and a detail_request naming the full call (NF-2026-01830). Error and no-records results pass through untouched.

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_task_usage_report"
  }
}

Input Schema

NameRequiredDescriptionDefault
fullNoTrue returns the raw core report; default False replaces stdout with a bounded summary.
topicNoOnly report usage for this topic; omit for all topics.
runnerNoOnly report usage by this runner; omit for all runners.
statusNoOnly report usage recorded with this task status; omit for all statuses.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.77
    • addedInput schema / properties / full
      Added value: +{
+  "default": false,
+  "description": "True returns the raw core report; default False replaces stdout with a bounded summary.",
+  "title": "Full",
+  "type": "boolean"
+}
  2. Changed3 schema fields changedv0.12.67
    • addedInput schema / properties / runner / description
      Added value: +"Only report usage by this runner; omit for all runners."
    • addedInput schema / properties / status / description
      Added value: +"Only report usage recorded with this task status; omit for all statuses."
    • addedInput schema / properties / topic / description
      Added value: +"Only report usage for this topic; omit for all topics."
  3. First observedv0.1.0

TDQS

A3.9/5.0
Behavior5/5

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

Annotations only declare readOnlyHint and openWorldHint, and the description goes well beyond them: it explains that the default truncates stdout to a header line, per-runner aggregates, and a top-20 record slice, exposes a detail_omitted fingerprint plus a detail_request, and states that error and no-records results pass through untouched. That is exactly the kind of payload-shape and degradation behavior an agent needs before deciding how to call it.

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

Conciseness3/5

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

The purpose line is front-loaded, but the body is a dense, jargon-heavy paragraph relying on phrases like "exactly as before" and an unexplained ticket reference "(NF-2026-01830)" that convey nothing to a fresh agent. It is informative but not tight; the truncation detail could be stated in half the words.

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?

With an output schema present and annotations covering safety, the description only needs to explain the non-obvious summarization behavior, which it does thoroughly. It is slightly incomplete in never stating what the report actually measures (tokens/cost per task) or how filters combine, but nothing critical to invocation 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 100%, so the schema already documents all four parameters, but the description adds real meaning about `full`: it spells out what the bounded summary contains, which the schema only summarizes in one clause. The topic/runner/status filters are left entirely to the schema, which is acceptable given full coverage.

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?

The opening sentence names a specific verb and resource ("Return task usage report") and mentions optional filtering, so an agent knows it retrieves usage metrics. It does not differentiate itself from near-neighbors such as aiworkhub_task_cost_ledger or aiworkhub_manager_skill_usage, which also expose cost/usage data.

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?

Guidance is limited to "optionally filtered" plus the parameter-level filters; there is no statement of when to prefer this over the cost-ledger or skill-usage siblings, or when the summarized vs. full payload is appropriate. Usage is implied by the filters rather than explained.

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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