extract_contact

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

No annotations are provided, so the description carries the full behavioral burden, yet it says nothing about output shape, what happens when no name/email/phone is found, or whether multiple contacts in the blob are handled. The trailing '[conductor: verified stochastic command]' hints that results may be non-deterministic but is too cryptic to be actionable for an agent.

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 operative sentence is front-loaded and wastes no words. The bracketed conductor annotation is noise that does not help an agent decide or invoke, slightly diluting an otherwise tight description.

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 annotations and no output schema, the description is the only source of truth, and it omits the return structure (object with three fields? nulls for missing values?) and failure behavior. For an extraction tool where the output contract matters most, that is a real gap.

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?

There is one required parameter with 0% schema description coverage, so the description must compensate. Calling the input 'a blob of text' clarifies it is raw free-form text rather than structured fields, but it gives no hints about size limits, encoding, or how much surrounding text is tolerable.

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 (extract) and resource (a contact's name, email, and phone) from input text, which is concrete enough to distinguish it from broader siblings like summarize or classify_sentiment. It does not explicitly contrast itself with near-neighbors such as extract_emails or normalize_phone, so sibling differentiation is only implied by the three-field scope.

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?

There is no guidance on when to pick this over extract_emails (email only), normalize_phone, or redact_pii. The description says what it pulls out but never states prerequisites, when-not-to-use, or which sibling handles the narrower cases.

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