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AIWorkhub

AIWorkhub

by shrec
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

aiworkhub_quality_run_checks

Gate changes by running repo-declared build, test, lint, and typecheck commands from .aiworkhub/quality.json, optionally scoped to changed paths; malformed config fails closed.

Instructions

Run repo-declared .aiworkhub/quality.json build/test/lint/typecheck commands (argv arrays only, shell=False). Fails closed on malformed config. Diff/new-code-first: pass changed_paths to scope evidence. Use to gate a change on the declared checks; read the declared profile first if unsure what is declared.

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_quality_run_checks"
  }
}

Input Schema

NameRequiredDescriptionDefault
changed_pathsNoRepository-relative paths changed by the task; scopes which declared checks apply and is recorded as each check's affected_paths. Omit to run the checks unscoped.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.67
    • addedInput schema / properties / changed_paths / description
      Added value: +"Repository-relative paths changed by the task; scopes which declared checks apply and is recorded as each check's affected_paths. Omit to run the checks unscoped."
  2. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Beyond the annotations (readOnly=false, destructive=false, openWorld=false), the description discloses meaningful execution behavior: argv-array-only invocation with shell=False, fail-closed handling of malformed config, and diff/new-code-first scoping recorded per check. These are real operational details an agent could not infer from the annotations. It still doesn't say what a failing check returns or whether the run is sandboxed.

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?

Four short sentences, front-loaded with the core action and followed by constraints, scoping, and usage in a logical order. The compact parenthetical '(argv arrays only, shell=False)' and 'Fails closed on malformed config' each carry real information without padding.

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, the description needn't explain return values, and it covers config source, execution semantics, failure mode, and scoping. The main remaining gap is environment/prerequisite context (e.g., whether the quality config must exist or what occurs if no checks are declared), which is only partially implied by 'fails closed on malformed config.'

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

Parameters3/5

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

Schema description coverage is 100% and the single parameter already documents scoping and affected_paths recording. The description's 'Diff/new-code-first: pass changed_paths to scope evidence' largely restates the schema, adding only the diff-first framing rather than new syntax or edge-case semantics. Baseline 3 is appropriate.

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 description opens with a specific verb and resource ('Run repo-declared .aiworkhub/quality.json build/test/lint/typecheck commands'), so an agent knows exactly what executes and where the command definitions come from. It implicitly separates itself from siblings like quality_reviewer_launch or quality_evidence_packet by framing the tool as running declared checks, but it never names an alternative tool explicitly.

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?

'Use to gate a change on the declared checks' gives a clear condition for invocation, and 'read the declared profile first if unsure what is declared' handles the ambiguity case. There is no explicit when-not-to-use guidance (e.g., when to prefer the evidence packet or reviewer launch instead), which keeps it out of the top band.

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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