read_chunk

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

No annotations provided, so the description carries full burden. It discloses that the chunk is validated against HEAD (relocating or flagging stale/gone), includes call-graph context and bound repo memories, and that distilled records are attached. This goes beyond a simple read and adds valuable behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The core action is front-loaded, and every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read tool with 5 parameters and no output schema, the description covers the primary purpose, validation, and return of distilled records. It lacks details on graph_limit and worktree, but the overall context is sufficient for most uses given sibling tool variety.

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

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

Schema coverage is 40%, so description must compensate. It mentions 'one chunk id' (chunk_id) and 'include' for memories, and 'compact call-graph context' hints at include_graph. However, it does not explain graph_limit or worktree, leaving gaps beyond schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies the exact verb 'Read' and resource 'source text for one chunk id', and distinguishes from siblings like memory_search or symbol_lookup by emphasizing validation against HEAD and compact call-graph context.

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

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

It states 'Use to read exact text after a search returns a chunk_id', giving a clear usage context. It does not explicitly mention when not to use or list alternatives, but the context is sufficient.

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