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LuisCarlosLopes

codesteer-atlas

atlas_brief

Orient yourself in an unfamiliar project with a pre-computed, ranked briefing covering identity, layers, entrypoints, and key connected files.

Instructions

Get a pre-computed, token-bounded briefing that orients you in an unfamiliar project.

Call this FIRST, once, when you start working on a project you do not already know. It replaces the usual orientation ritual (listing directories, reading the README, opening several files just to get your bearings) with a single small response.

Returns a ranked summary: identity (repo, language distribution, size), layers (the main directories, what role each plays, and their most important files), entrypoints (how the project is actually started), and hubs (the most connected files — the ones whose change propagates furthest). Every list is ranked and capped, so the response size does NOT grow with the size of the repository.

Do NOT call this to enumerate symbols or files: by design it reports at most a handful of layers and a few files per layer. Use atlas_search (optionally with path_prefix) to find a specific implementation, and atlas_graph to explore connectivity. Do NOT call it more than once per session — the briefing only changes after atlas_index re-runs.

Facts are derived deterministically from the index; nothing is guessed. Entries carry confidence (declared when read from a manifest such as pyproject/package.json, inferred when detected in code) and warnings reports known gaps, e.g. graph_unavailable, no_import_edges, low_symbol_coverage, index_stale.

Staleness is detected by comparing the indexed git HEAD with the current one, so uncommitted edits are not detected (same limitation as atlas_status).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelNoDetail level. `0` is a minimal orientation (identity plus directory roles); `1` (default) adds per-layer top files, entrypoints and hubs.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so excellently. It discloses deterministic derivation, response size capped independent of repo size, ranked/capped lists, confidence levels with declared vs inferred, known warning types, and staleness detection limitations including the inability to detect uncommitted edits.

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?

The description is longer than average but every sentence earns its place. It is front-loaded with a one-sentence summary, followed by explicit usage instructions, output details, and limitations, without redundant filler.

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 the tool's complexity and the absence of annotations, the description covers all necessary context: what it does, when to call it, what it returns, how to interpret results, known edge cases, and relationships to sibling tools. The output schema existence further reduces the need to explain return types, but the description goes beyond that anyway.

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%, so the baseline is 3. The description does not add new meaning about the `level` parameter beyond what the schema already says, though it enriches the overall understanding of the response shape (ranked, capped lists) which indirectly informs parameter expectations.

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 opens with a specific verb+resource: 'Get a pre-computed, token-bounded briefing that orients you in an unfamiliar project.' It clearly distinguishes the tool from siblings by explicitly naming atlas_search, atlas_graph, and atlas_index and stating what each is for.

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

Usage Guidelines5/5

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

It gives explicit when-to-use guidance ('Call this FIRST, once, when you start working on a project you do not already know'), what not to use it for, and names alternative tools for specific tasks. It also warns against repeated calls and notes when the briefing changes.

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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