Skip to main content
Glama

Run atlas generation

atlas_run

Trigger a full documentation generation run for all sources in an Atlas project: re-ingest, regenerate cited pages, and re-audit coverage. Returns run IDs for each source for status polling.

Instructions

Trigger a FULL doc-generation run for every source in an atlas project (project_id from atlas_list_projects): re-ingest the sources, regenerate the cited pages, and re-audit coverage. Management-level (project owner / org admin) — a run fetches the sources, spends LLM budget, and rewrites the generated subtree (creating the output space on the first run). Returns run_ids (one per source); poll each with atlas_run_status. Returns 503 ai_unavailable when the instance has no embedder/LLM configured.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesid of the atlas project to generate docs for (from atlas_list_projects)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idsYes
Behavior4/5

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

Discloses key behaviors: fetches sources, spends LLM budget, rewrites generated subtree, creates output space on first run, returns run_ids and 503 error. Adds value beyond annotations which only indicate non-destructive and non-read-only.

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?

Concise, front-loaded with purpose, and every sentence adds value—no redundancy or fluff.

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?

Given presence of output schema, description sufficiently covers return values (run_ids) and error conditions (503 ai_unavailable), along with permissions and side effects.

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 covers project_id with description, and the description reinforces where to obtain it ('from atlas_list_projects'), aiding in parameter selection and reducing ambiguity.

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?

Description clearly states it triggers a full doc-generation run for all sources in an atlas project. Specific verb 'trigger', resource 'atlas project', and differentiates from sibling tools like atlas_run_status and atlas_list_projects.

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?

Explicitly states management-level access requirement (project owner/org admin), mentions spending LLM budget, and explains the 503 error condition. Lacks explicit when-not-to-use guidance but provides strong context for appropriate use.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/zcag/tela'

If you have feedback or need assistance with the MCP directory API, please join our Discord server