Skip to main content
Glama

xmp4 — Semantic code knowledge for your stack

by ai.example4

xmp4_search

Search symbols in a project. Use xmp4_projects first to find the project identifier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoFilter by kind: Class, Method, Function, etc.
pageNoPage number (1-based, default 1)
queryYesSearch query (symbol name or pattern)
projectYesProject id: 'repo/project' or 'repo/project/language'. Case-insensitive prefix match. Append '/Python'|'/CSharp'|'/Java'|etc. only to disambiguate multi-language projects (e.g. 'django/Django/Python' vs 'django/Django/JavaScript'). 1 match → proceeds; N → warning lists candidates; 0 → do NOT iterate guesses, call xmp4_projects(query=...) once then retry.
page_sizeNoResults per page (default 20, max 100)
max_resultsNoMaximum results to return (default: 50). Kept as per-page upper bound alongside page_size.
output_formatNoOutput format: Compact (default) or Verbose

TDQS

B3.4/5.0
Behavior2/5

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

No annotations exist, so the description carries the burden. It only states the purpose and prerequisite, not behavior like pagination, result format, or error handling. For a search tool, it should at least hint at output characteristics.

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?

Extremely concise: two short sentences. Front-loaded with the core purpose, no wasted words.

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 7 parameters, no annotations, and no output schema, the description is too sparse. It lacks information on return values, pagination, or error behavior. The schema covers params but the overall tool context is incomplete.

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%, with rich descriptions for params like 'project' explaining disambiguation. The description adds no extra parameter semantics beyond the prerequisite. Baseline 3 applies.

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 states 'Search symbols in a project' with a clear verb and resource. It distinguishes itself from text search (xmp4_grep) by focusing on symbols, though it doesn't explicitly contrast sibling tools.

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?

It provides a clear prerequisite: 'Use xmp4_projects first to find the project identifier.' This tells the user when to use the tool and a necessary precondition. It doesn't mention exclusions or alternatives, but the context is clear.

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

All xmp4 — Semantic code knowledge for your stack toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct purpose: callers vs callees vs usages vs tests_for are directionally different, grep vs search separates text from symbol queries, and outline/view/source/info each serve unique functions. No two tools clearly overlap.

Naming Consistency5/5

All tools follow a uniform 'xmp4_<snake_case_noun>' pattern with no mixed conventions or camelCase. The names are terse, descriptive, and predictably formatted.

Tool Count4/5

At 16 tools, this is slightly above the typical well-scoped range (3–15), but the breadth is justified by the comprehensive code-knowledge domain. Every tool covers a distinct feature, so the count feels reasonable rather than bloated.

Completeness5/5

The surface is remarkably complete for semantic code analysis: project discovery (xmp4_projects), symbol lookup (xmp4_search, xmp4_symbol_at, xmp4_info), navigation (xmp4_outline, xmp4_view, xmp4_source), relationship exploration (callers, callees, hierarchy, usages, tests_for), and supporting meta tools (guide, server, deps, grep). No obvious gaps exist for its stated purpose.

Resources