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ProxyKit-mcp

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Run local workflow

run_ai_workflow
Read-only

Run deterministic local workflows over ProxyKit engine data to explain failures, generate issues or mocks, suggest tests, and summarize sessions; returns markdown for agent chaining.

Instructions

Run one of ProxyKit's built-in local workflows over engine data. These workflows are deterministic — they do not call an external LLM. Returns markdown the agent can chain into its own reasoning ("explain_failure → generate_issue → suggest_tests").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entry_idNoTraffic entry id. Required for explain_failure, generate_issue, generate_mock.
workflowYesOne of: explain_failure, generate_issue, suggest_tests, summarize_session, generate_mock.
session_idNoSession id. Required for summarize_session and suggest_tests (candidate).
baseline_idNoBaseline session id. Required for suggest_tests.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

The annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuine value beyond that: it flags determinism, explicitly rules out an external LLM call, and states the return format (markdown). It stops short of noting any rate limits or failure behavior.

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?

Three front-loaded sentences with no filler; purpose, a key behavioral qualifier, and the output/chaining hint come in that order. The parenthetical chain example is slightly cryptic but still earns its place.

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 correctly steps in to state the return type (markdown) and how it is meant to be consumed. Combined with 100% schema coverage, an agent has enough to invoke this correctly, though the per-workflow input requirements are only in the schema, not the description.

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 schema explains required/optional entry_id, session_id, and baseline_id per workflow. The description adds no parameter-level detail, so the baseline of 3 for a fully-documented schema applies.

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 clear verb (Run) and resource (ProxyKit's built-in local workflows over engine data), and the deterministic/no-LLM clarification sharpens what kind of operation this is. No sibling in the list performs workflow execution, so no explicit differentiation is needed. The absence of the actual workflow names from the description is a minor gap, but the schema carries them.

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 chaining hint ("explain_failure → generate_issue → suggest_tests") implies a pipeline usage pattern, but the description never states when to reach for this tool versus doing analysis manually, nor any prerequisites. Usage is implied rather than stated, which lands at minimum-viable.

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