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verify_task

Check an AI agent's work in a local git repository by recording a baseline, running relevant checks, and cross-checking claims to return an evidence-labelled verdict and next prompt.

Instructions

Full pipeline: inspect changes, run relevant checks, cross-check the agent's claims, and return a compact evidence-labelled handoff with a verdict and a suggested next prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoOptional free-text notes to include in the handoff.
claimsNoStatements about the work to check, e.g. 'fixed login redirect in auth.py'.
formatNomarkdown (compact handoff) or json (full structured report).markdown
repo_pathYesAbsolute path to (a directory inside) the git repository.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false and destructiveHint=false; the description explains why it is not read-only by noting it 'run[s] relevant checks', which resolves a potential ambiguity. It also discloses the output shape (evidence-labelled handoff, verdict, suggested next prompt), which the annotations do not cover. It does not contradict the annotations.

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?

A single front-loaded sentence enumerating the pipeline stages with no filler. Efficient and appropriately sized, though the dense clause list is not broken up for scannability.

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 no output schema, the description usefully characterizes what is returned (compact handoff, verdict, next prompt), filling the return-value gap. For a complex pipeline tool with four fully documented parameters, little is missing beyond explicit sibling routing.

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%, so the schema already documents repo_path, claims, notes, and format. The description only obliquely references 'the agent's claims' and adds no syntax, format, or default details beyond the schema. 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 states specific verbs and resources: inspect changes, run checks, cross-check claims, and return a handoff with a verdict. Calling itself a 'Full pipeline' distinguishes it from the piecemeal siblings (run_relevant_checks, summarize_handoff) implicitly. It stops short of explicitly naming those siblings, so it is clear but not fully differentiated.

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 'Full pipeline' framing implies this is the end-to-end option versus the granular siblings, but there is no explicit when-to-use/when-not guidance or named alternative. The agent must infer that this bundles inspect_task_state, run_relevant_checks, and summarize_handoff.

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