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kintsugi_scan_code

Scans inline code or file paths against verified AST and regex guardrails before writing or committing, catching known anti-patterns early.

Instructions

Deterministically scan a source snippet or file path against verified Kintsugi Golden Scars (AST + Regex) before writing or committing.

Input Schema

NameRequiredDescriptionDefault
codeNoInline source code to scan
languageNoOptional language override (python, typescript, javascript, shell, markdown)
file_pathNoPath on disk to scan (or virtual filename for language detection)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully signals determinism (no LLM inference) and the AST+Regex mechanism, but never states that the operation is read-only/non-mutating, nor what the result looks like or what happens when a scar matches. Key behavioral context is missing for an un-annotated tool.

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 with no filler, and the timing constraint is placed at the end where it reads naturally. 'Kintsugi Golden Scars' is domain jargon left unexplained, which slightly reduces immediate comprehensibility.

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

Completeness3/5

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

With no output schema and no annotations, the description should say what a scan yields (findings list? boolean verdict?) and how matches are reported. It covers what to scan and roughly when, but leaves the caller unable to predict the response shape.

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 coverage is 100%, so the baseline is 3. The description adds only marginal meaning by framing 'code' and 'file_path' as alternative input modes ('snippet or file path'); it says nothing about precedence when both are supplied or how 'language' interacts with file_path detection.

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 pairs a specific verb ('scan') with concrete inputs ('source snippet or file path') and a named rule set ('Kintsugi Golden Scars (AST + Regex)'). It is clearly distinguishable from the siblings (list_scars, record_failure, compile_skills), though it never explicitly contrasts itself with 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?

There is an implicit usage trigger — 'before writing or committing' tells the agent this is a pre-write gate. But there is no guidance on what to do with a match, no when-not-to-use condition, and no routing to siblings such as record_failure after a finding.

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