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DarkMatterProductions

mcp-project-context-server

search_adr_sections

Use natural language to find relevant sections within a specific ADR, scoped by number or filename.

Instructions

Semantically search within a single resolved ADR, scoped by number or filename. Use this to find relevant sections/passages inside one ADR you've already identified (e.g. via list_adrs or search_adr_index).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query
n_resultsNo
project_pathYesAbsolute filesystem path, a short 'owner/repo' identifier, or a full https:// repository URL.
number_or_filenameYesThe ADR's number (e.g. 12), short form (e.g. 'ADR-00012', case-insensitive), or exact filename/path (e.g. 'ADR-00012-topic.md').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYesIndividual matching hits, one per matched chunk.
warningNoPresent only when the index was built with a different embedding provider/model.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the burden. It conveys that this is a semantic, scoped search and implies read-only behavior, but it does not explain preconditions or what 'resolved' means, nor what happens when no matches are found.

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?

Two sentences with no filler. The core action and scope are front-loaded, and the usage hint about prior discovery tools is immediately useful.

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?

Combined with the input schema and output schema, the description gives an agent enough to call the tool successfully: scope, prerequisite identification step, and query semantics. Minor gaps around alternatives and result behavior are not critical.

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 75%, so the schema already documents most parameters. The description adds context that `number_or_filename` is the scoping mechanism and that the ADR should already be identified, but it adds no detail about `n_results` beyond the schema default.

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?

States a specific verb ('semantically search'), resource ('a single resolved ADR'), and scope ('by number or filename'). The phrase 'inside one ADR you've already identified' clearly differentiates it from searching the index across multiple ADRs.

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 clear context: use it after identifying an ADR via `list_adrs` or `search_adr_index`. It does not explicitly state when not to use it or name alternative section-listing tools like `list_adr_sections`, but the intended usage is clear.

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