Audit the current engagement for red flags

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

No annotations are present, so the description carries the full burden and largely succeeds: it discloses the output contract (severity-tagged flags, concrete recommendations, named inferred/untraceable entries, counting behavior) and a notably nuanced rule — positives are only reported when at least one entry can actually be pointed at in the original, guarding against fabricated 'good news'. The verb set (report, count, name, return) strongly implies a read-only operation, though it never explicitly states that engagement data is unchanged.

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 English text is dense and well front-loaded: the first sentence states the core purpose and deliverables, the second adds traceability counting and naming, the third the nuanced positives rule — every clause earns its place. The full Japanese duplicate roughly doubles length, but this appears intentional given the tool exposes a lang parameter (ja/en/both) and serves a bilingual audience.

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?

With no output schema and no annotations, the description carries the completeness burden and compensates well: it specifies exactly what the tool returns — severity-tagged red flags with recommendations, traceability counts, named inferred entries, and a guarded positives section. The exact output rendering (e.g., structured list vs. prose report) is unstated, and 'current engagement' relies on a system-level concept established by siblings, but the behavioral contract is clear enough for an agent to invoke and interpret results 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 description coverage is 100% — both asOf (date pattern, default 'today') and lang (enum with default 'both') are fully documented in the schema. The description adds no parameter-level detail, but the baseline of 3 applies because the schema already carries the full burden; no compensation 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?

States a specific verb and resource — 'Audit the current engagement' — and enumerates concrete deliverables: red flags (missing sponsor, unowned high risks, overdue actions, unapproved key deliverables, empty registers) with severity and recommendations, plus source-traceability counts and a guarded positives section. The specificity makes the purpose unmistakable and effectively differentiates it from siblings like check_intake, inspect_findings, or review_all_engagements, even without naming them.

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 conveys clear context — run this to audit the currently active engagement for practical red flags — and the 'current engagement' framing signals its scope. However, it never states when not to use it or names an alternative for overlapping concerns (e.g., inspect_findings for findings-level review, check_intake for intake status). Usage is implied by the tool's name and audit framing rather than explicitly routed.

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