DatasheetVend

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It reveals determinism ('No LLM is involved'), caching behavior ('cached by SHA-256, so repeat calls are instant'), page-number semantics, and the need to check review.required and warnings before trusting a degraded map. This is substantial, non-obvious behavioral context.

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?

Though lengthy, the description is dense and every sentence earns its place. The core definition is front-loaded, followed immediately by usage priority, exclusion guidance, page-number semantics, and trust caveats. There is no filler, repetition, or vague prose.

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?

Despite lacking an output schema, the description names the key return elements an agent must use: anatomy.dominant_form for tool selection, review.required, warnings, and the per-page geometry census. It also explains the cache behavior and physical page numbering. For a one-parameter tool, this is complete enough to call and use 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?

There is only one parameter, documentPath, and the schema description already defines it as an absolute filesystem path or https URL. The tool description adds that it is a datasheet PDF, which is consistent but not materially new information. With 100% schema coverage, the baseline of 3 is appropriate.

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 a specific verb and resource: 'Build the Document Map of a datasheet PDF.' It enumerates the map's contents (topic locations, page physical forms, geometry census) and explicitly differentiates itself from a sibling by saying 'use extract_pinout for pins.' An agent cannot confuse this with the other tools.

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?

It gives explicit when-to-use guidance ('USE IT FIRST, before reading any page of a datasheet'), what to do next with the map ('read the candidate pages it recommends and pick your tool per page from anatomy.dominant_form'), and what not to use it for ('Do NOT use it to get pin names, dimensions, or ratings'). It even names the alternative tool for pins.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the output shape (PinoutEvidence document), the presence of a review-state, and the specific condition under which human review is required (e.g., no pins recovered or warnings raised). It does not mention side effects or permissions, but for an extraction tool this is sufficient and adds meaningful context beyond the schema.

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 three sentences, with the core purpose stated first and then the output contract and usage guidance following. Every sentence earns its place and there is no redundant or filler content. It is dense but well-structured.

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?

Despite lacking an output schema, the description explains what the return value is (PinoutEvidence document), what it contains (canonical pins, special pads, names/types/functions), and how to interpret it (review.required flag). It also gives usage guidance and connects to the datasheet PDF context. Nothing critical is missing for an agent to invoke the 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?

The schema already provides 100% description coverage for all three parameters, so the baseline is 3. The description does not add parameter-level detail beyond what the schema already states, but it also does not need to. It provides domain context by explaining that the extraction is from a datasheet PDF for a component.

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 verb ('Extract'), a specific resource ('a component's pin/pad table from a datasheet PDF'), and clarifies the unique value proposition ('verifiable, provenance-tracked evidence — not raw PDF text to re-interpret'). This clearly distinguishes it from generic PDF-reading tools and sibling tools.

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 says 'Prefer this over reading the PDF yourself', giving the agent a clear directive on when to use this tool. It also instructs the agent to 'trust review.required before acting on the pins'. However, it does not explicitly mention sibling tools or state when not to use this tool in favor of them.

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

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

With no annotations provided, the description carries the full burden and meets it: it explicitly states 'Read-only; never rebuilds, never bills' and discloses that include_physical returns very large payloads. This gives the agent strong expectations about side effects, cost, and performance.

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 information-dense but not bloated. Purpose is front-loaded, the workflow constraint follows immediately, and every sentence contributes either usage sequencing, parameter guidance, or behavioral disclosure. No filler or redundant restatement of the schema.

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 3-parameter, no-output-schema tool with no annotations, the description is complete: it explains when to call it, what it returns at a sufficient level, how to reference the document, how to handle the heavy flag, and the read-only/no-cost behavior. Nothing critical for correct invocation is missing.

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 100%, so the baseline is 3, but the description adds real value beyond the schema: documentRef is 'served free from cache' and the map result is the preferred source, while include_physical is tied to 'raw positioned tokens/vector paths' and a concrete payload-size warning.

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 opens with a precise verb/resource pairing: 'Tier-2 detail for ONE page of an already-mapped datasheet.' It enumerates exactly what the page-level inspection returns — measured anatomy, headings, first lines, and module claims — and distinguishes it from the Tier-1 map, so an agent can immediately tell it apart from sibling tools.

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 gives explicit sequencing: use AFTER extract_document_map, when the Tier-1 index says a page matters and its one-line summary is insufficient. It also provides the prerequisite input (document.sha256 from the map) and warns when the heavy include_physical option should or should not be enabled.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly discloses that the returned content is static per contract version and that repeated calls are unnecessary. It could go further by stating that this is a read-only operation with no side effects, but the static and session-scoped guidance covers the most important behavior.

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?

Two sentences deliver all essential information with no filler. The content list is front-loaded, and the usage warning occupies the second sentence without redundancy.

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 tool with no output schema, the description is complete: it names the return contents, specifies when to call it, and explains why repeated calls are unnecessary. Nothing an agent needs to invoke it correctly is missing.

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 no parameter semantics to clarify. The schema coverage is trivially 100% as an empty object, and the description adds useful context about what the returned instructions contain.

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 uses a specific verb ('Return') and a specific resource ('versioned usage instructions for Document Map consumers'), and enumerates the actual content: binding rule, field semantics, dominant_form action table, and routing discipline. This clearly distinguishes it from sibling tools like extract_document_map, which extract maps rather than returning instructions.

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 states exactly when to call it ('once per session before working with maps from extract_document_map') and explicitly warns against repeated calls because the text is static. This is direct usage guidance that an agent can act on without inference.

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