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UnboundCompute

lachesis-mcp

Official

change_context

Retrieve commit history for any symbol—see who last modified it and when. Returns author, date, and subject for each change, newest first.

Instructions

Read-only. Join a symbol to its Git history: the exact commits that touched it with author, date, and subject. Returns history facts only — no generated 'why' narrative. Use it to date a change or find who last touched a function; newest first, paged with limit/offset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNomaximum commits returned
formatNotext (compact, default) | json (structured result page)
offsetNocommit offset for paging
symbolYessymbol name or graph node id

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changedv0.2.0
    • addedInput schema / properties / limit / description
      Added value: +"maximum commits returned"
    • addedInput schema / properties / offset / description
      Added value: +"commit offset for paging"
    • addedInput schema / properties / symbol / description
      Added value: +"symbol name or graph node id"
  2. First observedv1.0.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so well. It states read-only access, the exact facts returned, the absence of generated interpretation, newest-first ordering, and paging via limit/offset. This gives the agent a strong mental model of the tool's behavior beyond any structured metadata.

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

Conciseness5/5

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

Three compact sentences front-load the most important fact ('Read-only'), then state purpose, constraints, use cases, and behavior with no filler. Every clause earns its place.

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

Completeness5/5

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

For a four-parameter tool with no output schema and no annotations, the description is unusually complete: it covers safety, return contents, output style, ordering, paging, and intended use. An agent has enough context to select and invoke this tool correctly.

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 baseline is 3; the schema already explains symbol, limit, offset, and format. The description adds 'newest first' ordering and confirms paging semantics, but it does not meaningfully expand parameter meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource ('Join a symbol to its Git history') and clearly states the output: exact commits, author, date, subject. It also differentiates itself from explanation-style siblings by explicitly saying it returns history facts only and no generated 'why' narrative.

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?

Gives concrete use cases: 'date a change or find who last touched a function'. It also implicitly tells the agent when not to use it by stating 'no generated why narrative'. However, it never names an alternative tool for those narrative cases, so it stops short of fully explicit when-not guidance.

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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