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lexicon_search

Search a local archive of curated project notes, repo docs, and session transcripts to find prior work, past decisions, and failed approaches before solving a nontrivial problem.

Instructions

Search the Lexicon: curated project notes, in-place repo documentation, and archived Claude Code / Codex / ChatGPT session transcripts. Hybrid lexical (FTS5) plus semantic (local embeddings) search. Use before re-solving a nontrivial problem to find prior work, past decisions, and approaches that already failed.

Reading the results: score is ordinal and only orders one result set against another in the same query -- it says nothing about whether the Lexicon actually covers the topic. confidence does: it is absolute, runs 0.15-1.00, and is comparable across queries. At or above 0.80 the corpus genuinely covers the point; between 0.60 and 0.80 treat the result as partial or tangential and verify before relying on it. If most results sit below that, the honest answer is that the Lexicon does not cover this -- say so instead of stretching a weak hit. matched_by shows which leg found it: fts is an exact lexical match, vector a semantic one, and both together is the strongest signal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNoISO date lower bound, YYYY-MM-DD
limitNoMax results
queryYesWhat to look for. Quote exact identifiers, paths, error strings or symbols to force an exact lexical match.
beforeNoISO date upper bound, YYYY-MM-DD
projectNoRestrict to one project. Historical and alias names resolve to the current project (a renamed repo's old name resolves to its new one).
source_typeNolexicon = curated notes; repo-doc = docs in a live repo; transcript = archived sessions (Claude Code, Codex, Claude/ChatGPT web); codex-memory / claude-memory = distilled memory stores; claude-project = Claude project briefs and their attached docs.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.3.0

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations provided, the description takes full responsibility for behavioral disclosure and does so thoroughly. It explains the meaning of the score field (ordinal, query-relative), the confidence field (absolute, comparable, with actionable thresholds 0.80 and 0.60-0.80), and the matched_by field, including what signals the strongest match. This goes well beyond a basic statement of behavior.

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?

The description is long but every section earns its place: purpose, when to use, and a compact but essential guide to interpreting results. The confidence threshold guidance is front-loaded after the purpose and prevents wasted effort on weak hits. No filler or tautology is present.

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?

The description is effectively complete for a search tool. It covers what is searched, when to search, how to interpret the returned fields, and how to handle the 'corpus not covered' case. The schema handles parameter details and an output schema exists, so the description must focus on decision-making semantics, which it does.

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 input schema already documents all six parameters adequately. The description reinforces the query technique of quoting exact identifiers, paths, or error strings, but adds no new parameter-level semantics beyond what the schema provides. This matches the baseline of 3 for full schema coverage.

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 clearly identifies the action ('Search the Lexicon') and the specific resource scope ('curated project notes, in-place repo documentation, and archived session transcripts'). It is clear that this tool searches rather than reads, but it does not explicitly mention or differentiate the sibling tool lexicon_read, so it misses the full 5.

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?

The description gives an explicit when-to-use directive: 'Use before re-solving a nontrivial problem to find prior work, past decisions, and approaches that already failed.' It provides clear context for when the tool is appropriate, but does not state exclusions or contrast with lexicon_read, so it stops short of a 5.

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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