check_self_narration

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

With no annotations present, the description carries full behavioral disclosure and does so thoroughly: it states 'read-only, no LLM', explains the pollution problem it addresses, and explicitly says 'Flags, never blocks' to manage expectations about failure modes. The return shape {'self_narration': bool, 'markers': [...]} is disclosed, giving the agent a precise contract.

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?

The description is dense but every clause adds value: the label, the semantic question, the motivation, the return format, and the blocking behavior. The structure front-loads the core purpose and ends with a crisp behavioral note. No filler or repetition.

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 single-parameter, deterministic check with no output schema and no annotations, the description fully covers what the tool does, what it returns, when to use it, and what its side effects are. An agent has everything needed to select and invoke this tool correctly.

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 0%, so the description must compensate, and it does: 'text' is clearly identified as the 'candidate memory' to be evaluated. The description does not spell out limits like max length or encoding, but for a single obvious string parameter this is sufficient to invoke the tool correctly.

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 states a specific action (check for self-narration), the resource (candidate memory), and the exact semantic distinction being tested ('assistant narrating its own reasoning/state' vs 'a fact about the user/world'). It also clearly separates this guard from siblings like check_conflict and verify_claim by tying it to the memory-writing path.

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?

The description explicitly frames the tool as a 'WRITE-TIME' guard and instructs that it should be used before remember(): 'gate or rewrite the write before remember()'. It does not explicitly name alternatives or when-not-to-use, but the write-time context is clear enough for an agent to choose it over other checking tools.

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