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lexical_lookup

Read-onlyIdempotent

Search stored graph fields for exact literal matches, punctuation included, to return lexical evidence for code and relationship queries.

Instructions

Exact literals, punctuation included, in stored graph fields. Lexical evidence only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoEntity kind; test means test role.
limitNoHits per page.
cursorNoNext page; restart if contents changed.
literalNoBare literal; ASCII case-insensitive.
max_charsNoSoft cap on reply bytes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.17

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds the meaningful behavioral detail that matching is exact (punctuation-sensitive) rather than fuzzy, but says nothing about pagination behavior, result shape, or how the soft byte cap truncates the response.

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?

Two short sentences, purpose and matching semantics front-loaded, with zero filler. It is arguably too terse for a five-parameter tool, but nothing is wasted.

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

Completeness2/5

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

With five parameters, no output schema, and no required parameters, the description should say something about what a hit looks like and how limit/cursor/max_chars interact with the returned graph fields. It leaves the entire result contract to inference, which is a notable gap given there is no output schema to fall back on.

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 all five parameters are already documented, and 3 is the baseline. 'Punctuation included' does sharpen the interpretation of the literal parameter, but the description adds no meaning for kind, limit, cursor, or max_chars.

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 specific matching mode (exact literals, punctuation preserved) against a specific resource (stored graph fields), and 'Lexical evidence only' implicitly separates it from the semantic_* siblings. It stops short of naming the operation verb or the field/entity scope being searched, so it is clear but not fully differentiated.

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?

'Lexical evidence only' implies the contrast with semantic_search/semantic_locate, giving an implied routing rule. However, it never states when to prefer lexical over semantic retrieval, and no alternative is named explicitly.

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