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Glama

trawl_build_graph

Builds or rebuilds a client's knowledge graph in the background, extracting entities and relations from pool chunks with configurable workers, providers, and an optional test sample.

Instructions

Build or rebuild the knowledge graph for a client. Runs in background.

Input Schema

NameRequiredDescriptionDefault
sampleNoProcess only N chunks (for testing)
rebuildNoClear and rebuild from scratch (default: false)
workersNoNumber of extraction workers
pool_nameYesPool to build graph for
providersNoOptional comma-separated provider allowlist (e.g. 'kimi,haiku'). When set, the LLM used for graph extraction must come from this list or the job fails. Accepts: local, kimi, gemini, haiku, sonnet, opus.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.4.1

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose that the job 'runs in background', which is genuine behavioral value (call returns before completion). It does not say what is returned (job id?), how to track progress, cost/duration, or what happens to an existing graph when rebuild is false.

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, front-loaded sentences with no filler. The brevity is close to under-specification, but nothing present 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?

This is an asynchronous, potentially expensive mutation job with no annotations and no output schema, so the description should explain the return value (job handle), progress tracking, and side effects on existing graph data. It gives only 'runs in background', leaving an agent unable to know how to follow up.

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 each of the five parameters is already documented, including the provider allowlist and sample limit. The description adds nothing beyond the schema, so 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?

States a specific verb (build/rebuild) and resource (knowledge graph), which distinguishes it from siblings like trawl_graph_stats, trawl_graph_export, and trawl_graph_prune. However, the phrase 'for a client' does not match the required parameter 'pool_name', leaving a small ambiguity about what is being built.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No indication of when to use this versus trawl_reindex_pool, trawl_sync_pool, or trawl_graph_stats, and no prerequisites or exclusions are given. The only guidance is the implicit 'rebuild' semantics already in the schema.

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