evaluate_trust_chain

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

With no annotations, the description fully describes the tool's behavior: it returns a JSON with specific fields (source_hashes, graph_hash, etc.) and explains the ROI gate logic. It does not disclose side effects or state changes, but the tool appears to be read-only. No contradictions.

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 well-structured with bullet points for trust chain components, front-loading the purpose. It is moderately long but each sentence adds value. Could be slightly more concise but overall appropriate.

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?

Given the complexity of trust chain evaluation and ROI analysis, and the presence of an output schema (ckg-trust-chain-v1), the description covers the key aspects: return format, decision rule, and trust chain fields. It is complete enough for an autonomous agent, though the output schema details are not elaborated.

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 has zero parameters, so schema coverage is 100%. Per the rubric, 0 parameters gives a baseline of 4. No additional parameter information is 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?

The description clearly states the tool returns a machine-readable JSON trust chain with ROI analysis and payment recommendation, specifying it's for autonomous agent consumption. It distinguishes itself by listing unique trust chain components that close the audit gap, differentiating from sibling tools like list_concepts or search_concepts.

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 provides explicit guidance on when to use this tool: for autonomous agents to evaluate trust, compare ROI, and autonomously purchase. It explains the decision rule (ROI gate) and mentions budget pre-authorization. However, it does not explicitly state when not to use it or compare to siblings.

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