paper_close_corpus

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

With no annotations, the description does disclose the key state change: the session corpus is discarded and discovery mode reverts to cwd/config. It does not say whether closing an already-closed corpus is an error, whether the corpus state is recoverable, or what is returned, which matters for a state-clearing operation.

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?

A single short sentence with the action front-loaded and the effect trailing. No filler, nothing to trim.

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 zero-parameter, no-output-schema tool, the description covers what it does and what state changes. A brief note on what happens if no corpus is active would make it fully self-contained.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies; no parameter information is missing or needed.

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?

States a specific action (close/forget the session corpus) and its consequence (return to cwd/config discovery). It implicitly contrasts with the sibling paper_open_corpus, but never names it, so the pairing has to be inferred rather than read.

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?

Usage is only implied: an agent can infer this is used when finished with a session corpus or wanting to fall back to path-based discovery. There is no explicit when/when-not guidance and no sibling named. Adequate but leaves the routing decision to inference.

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