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Glama

Symvanta

by com.symvanta

map

Read-onlyIdempotent

Token-efficient repo (or subtree) skeleton: directory tree with each file's classes (methods in parens), functions, and HTTP endpoints, from the graph. Orient before drilling in. Scope with "path", cap with "maxDepth", density:"full" adds properties. view:"architecture" instead returns a module map (Louvain clusters with hubs, paths and cross-module coupling), plus namedModules/totalModules: a module NAME comes from a generated summary and is provisional, its id (the member-set hash in the header) is the stable key, so pin modules by id and re-read names rather than caching them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoRepo-relative subtree (e.g. "src/v1/mcp"). Omit for the whole repo.
viewNo"tree" (default): file/symbol skeleton. "architecture": module map with hubs, coupling, cycles. Module names come from generated summaries: cite a module by its id (the member-set hash printed in the header), which is stable across calls and reindexes.
densityNo"compact" (default): classes/methods/functions/endpoints. "full" adds properties.
feedbackNoOptional: report how a previous answer worked out; piggybacks on any call.
maxDepthNoDrop files deeper than this many path segments. Omit for no cap.
commitShaNoPin reads to one indexed revision (7-40 hex). Graph tools error with revision_not_indexed when it is not an indexed revision of the scoped repository, or revision_not_servable when that revision's graph was superseded by a later reindex, and echo the revision served back as commitSha; source ops read git objects, so any commit works there. Exception: a kept revision (revisions rows flagged architectureSnapshot) still serves map view:"architecture" as a preserved snapshot.
projectIdNoProject id from init/list_projects. Omit for the active project.
repositoryNoRepository full name, e.g. "owner/repo". Omit when the project has one repository.

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly and idempotent hints, and the description adds substantial behavioral detail beyond that: output shape, token-efficiency, provisional module names with stable ids, and architecture-mode clustering behavior. This is exactly the kind of context an agent needs beyond structured annotations.

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?

The description is dense but every sentence contributes. The main purpose is front-loaded, and the parameter guidance is compactly woven in. The architecture-view sentence is long but packs essential caveats without waste.

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?

With no output schema, the description carries the burden of explaining return values, and it does so for both views: directory skeleton details and architecture module-map details. It also explains the module-name/id stability caveat and key parameter levers, making the tool callable without further inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real semantic value for path, maxDepth, density, and especially view—explaining what the architecture view returns and why module ids matter. It avoids repeating schema-only details for the remaining parameters.

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 clearly states what the tool returns: a token-efficient repo/subtree skeleton with classes, methods, functions, and HTTP endpoints. It also distinguishes the two views (tree vs architecture), making it easy for an agent to tell this orientation tool apart from sibling tools like source or list_file_symbols.

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 provides explicit usage context: 'Orient before drilling in' tells the agent when map is appropriate, and it explains how to scope, cap, and switch views. It doesn't explicitly name sibling alternatives or say when not to use it, but the guidance is clear enough for correct selection.

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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TDQS

A4/5.0
Disambiguation4/5

Tools generally target distinct operations—repository attachment, symbol resolution, graph traversal, source access, indexing health—and the detailed routing notes reduce ambiguity. A few pairs still overlap in intent (quick_lookup vs locate symbol, context vs ask_codebase), so it is not perfectly unambiguous.

Naming Consistency3/5

All names are lowercase snake_case and readable, but the set mixes verb_noun patterns like add_repository and list_projects with single-word nouns/verbs like context, history, map, relate, and source, plus one acronym (adr). There is no predictable convention across the full surface, though individual names are clear.

Tool Count3/5

25 tools is at the high end for a single MCP server and falls in the 'feels heavy' range. The breadth is justified by the code-intelligence/query domain, but the selection surface is large for an agent to navigate efficiently.

Completeness4/5

The code indexing, search, graph query, source access, history, ADR, test lookup, and scope estimation needs are well covered. Minor gaps remain—no detach/remove repository, no ADR content editing, and source access is gated by an add-on—but these are workable.

Resources