agentlab-services

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals that the tool is an independent QA notary and produces a signed pass/fail, but it omits critical details such as what 'signed' entails, whether it is read-only or writes a record, permission requirements, and what happens on failure.

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 a single, front-loaded sentence that clearly states the tool's purpose without waste. It is appropriately concise, though the terse phrasing leaves room for additional essential details that would not violate conciseness.

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 no output schema and no annotations, the description should explain the return format and how the deliverable is supplied. It fails to do so, leaving an agent without enough information to invoke the tool correctly and interpret its result beyond the high-level notion of a signed pass/fail.

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, and the schema description coverage is 100% (vacuously). The description adds no parameter information, which is acceptable given the absence of parameters; however, it does not explain how the deliverable to be checked is provided, which may be a hidden input gap.

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 (quality-check), resource (ANOTHER agent's deliverable), and outcome (issue a signed pass/fail), making the tool's function immediately understandable. It does not explicitly differentiate itself from siblings like notarize or honesty_audit, so sibling differentiation is left to inference.

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?

Usage is implied: the tool is for independently QA-ing another agent's deliverable. However, there is no explicit guidance on when to use this tool over alternatives, no exclusions, and no mention of prerequisites or context in which it is appropriate.

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, the description carries the full behavioral burden, but it does not disclose whether the audit is read-only, what permissions are needed, what it returns, or any side effects. 'Conservative' is the only hint at behavior, which is too vague to be actionable.

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 a single, front-loaded phrase with no wasted words. However, it is arguably under-specified rather than truly concise, which slightly limits its effectiveness.

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 no output schema, no annotations, and no parameters, the description should explain how the tool is invoked (e.g., what data it consumes) and what it returns. It does neither, leaving the agent with insufficient context to use the tool confidently.

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 defines zero parameters, so the schema cannot provide parameter semantics. The baseline for a zero-parameter tool is 4; the description adds no parameter-related meaning because none 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 states a specific analysis ('audit') on a specific resource ('work opportunity') and enumerates the dimensions checked (fit, fee, scam, eligibility, pay). It does not differentiate from sibling tools like honesty_audit or attest_quality, so an agent must infer the distinction.

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 explicit when-to-use guidance, no mention of alternatives (e.g., rank_opportunities, honesty_audit), and no preconditions. Usage is only implied by the phrase 'for a work opportunity,' leaving the agent to guess the appropriate context.

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?

No annotations are provided, so the description carries the full behavioral burden. It discloses only that the result is a 'tidy CSV'; it never defines what 'clean' or 'dedupe' mean operationally (which columns key the dedupe, how nulls/whitespace/encodings are handled), nor whether the input is mutated in place. For a transformation tool with zero annotation coverage this is a meaningful gap.

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?

A single front-loaded sentence that names the operations first and the return value second, with no filler.

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 zero declared parameters and no output schema, the description is the only place where input provenance and result format could be explained. It never says how the CSV is supplied or retrieved, nor what a 'tidy' output actually looks like, so an agent cannot invoke it correctly with confidence.

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 declares zero properties, so there are no parameter semantics for the description to add or omit. Baseline 4 applies for a parameterless tool.

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 concrete set of transformations (clean, dedupe, normalize) applied to a named resource (CSV) plus the output shape ('tidy CSV'). It is clear on its own, but gives no differentiation from any sibling — though the sibling list contains no other CSV tool, so there is little to differentiate against.

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 use this tool versus another approach, no prerequisites, and no exclusions. The agent must infer that it should reach for this whenever a CSV needs tidying.

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?

No annotations are provided, so the description carries the full behavioral burden. It usefully conveys that this is a non-mutating pre-flight screen covering three check categories, but says nothing about cost, auth requirements, latency, or what the verdict/response looks like.

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?

A single compact sentence, front-loaded with the key framing ('Verify-before-you-pay') and then the specific scope. Every clause earns its place with no 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 simple zero-param tool this is close to adequate, but with no output schema and no annotations, the description does not explain what the screen returns (verdict shape, pass/fail semantics). That is the main remaining 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?

The tool takes zero parameters, so there is no parameter semantics to document; per the baseline for 0-param tools, a 4 is appropriate. No described parameter meaning is missing.

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 names a specific verb (screen/verify) and resource (an x402 or MCP endpoint) and enumerates the checks performed (scam, liveness, https). It is clearly a verification tool, though it doesn't explicitly contrast itself with lookalike siblings such as attest_quality or trust_lease.

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 'Verify-before-you-pay' framing implies the triggering condition (pre-flight, before spending/committing) but never states when NOT to use it or which sibling to choose instead. Usage is implied rather than spelled out.

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?

No annotations are provided, so the description carries the full behavioral burden. 'Linter' and 'flags' imply a non-mutating analysis pass, but nothing states the return shape, whether findings are advisory or blocking, or how the text under audit is supplied. For an audit tool with a completely empty input schema, this is a significant disclosure gap.

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?

A single tight sentence with the core concept front-loaded and the three detection categories listed after the colon. It wastes no words, though the extreme compression leaves the input/output contract unaddressed.

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?

The description presents a tool that audits text, yet the input schema declares no properties and there is no output schema. Nothing explains how the target text reaches the tool or what comes back, leaving the call contract materially under-specified for an audit operation.

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 per the rubric the baseline is 4. There is no parameter surface for the description to explain, and nothing it says misrepresents the schema.

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 ('linter for AI output') and enumerates exactly what it detects: unsupported certifications, fabricated authority, uncited statistics. That is far more concrete than a tautology. It does not, however, differentiate itself from plausible siblings like verify_text or attest_quality, so it stops short of a 5.

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 phrase 'for AI output' implies a domain but gives no explicit when-to-use or when-not-to-use guidance, and no alternative is named despite several overlapping siblings (verify_text, attest_quality, screen_message). The agent must infer the boundary entirely on its own.

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?

No annotations are provided, so the description carries the full burden. It discloses the evidence sources (HN, StackExchange, GitHub), which is genuine context, but says nothing about output shape, freshness/live-fetch vs cached data, latency, or cost.

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?

A single tight sentence with the artifact and its sources front-loaded. No filler or 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?

The one-liner is adequate for a no-annotation, no-output-schema tool, but for a multi-source synthesis tool it leaves gaps: what the brief contains, how the topic is passed, and how it differs from auditing/ranking siblings. Not fully complete.

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 has zero formal parameters but additionalProperties is true, so the description's mention of 'for a topic' is the only indication of the required input. With 0 defined params, the baseline is 4; the topic hint adds useful value even though the exact argument name/format is unspecified.

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 names a concrete artifact (an evidence-backed demand/pain/opportunity brief) and its sources (HN, StackExchange, GitHub), which is more than a tautology. However, no verb is stated (generate/create/retrieve) and it never distinguishes itself from near-neighbors like audit_opportunity or rank_opportunities.

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 when-to-use, when-not-to-use, or alternative routing guidance. With siblings like audit_opportunity, rank_opportunities, and productize_service in the same domain, an agent has no explicit signal for choosing market_brief over 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, the description carries the full burden, and it does disclose the core behavior: it produces a receipt that is signed and timestamped. However it omits key traits — whether raw content is stored or only the hash, retention/immutability, and privacy implications of sending content to be notarized.

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?

A single dense sentence that front-loads the core concept ('Proof-of-existence') before the mechanism and use cases. Nothing is wasted.

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-param tool with no annotations and no output schema, the description omits how content is supplied (arguments? file?) and what exactly is returned or persisted. These are material gaps for a notarization primitive, though the core concept is conveyed.

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 are zero declared parameters, so the baseline is 4; the schema is open (additionalProperties: true). The description's 'binding any content to a hash' partially explains the freeform input, adding modest value over the empty schema.

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 outcome — a signed, timestamped receipt binding content to a hash — rather than a tautology on the name. It is clearly distinguishable from siblings like verify_text or attest_quality, though it never explicitly contrasts with 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 parenthetical '(IP/plagiarism/audit)' implies the scenarios the tool serves, which is real but only implied usage guidance. There is no explicit when-to-use/when-not, no prerequisites, and no routing to alternatives such as verify_text.

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?

No annotations are provided, so the description must carry the full behavioral burden. It only describes the output characteristics (fixed-scope, priced, machine-readable) and does not disclose what the tool does operationally, what permissions it requires, whether it is destructive, or what side effects occur.

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?

A single front-loaded sentence with no filler. It is appropriately concise for a no-parameter tool.

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 minimal. It gives some sense of the output but does not explain what input is expected or how to invoke the tool, leaving clear gaps for an agent to call it 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 has zero parameters, so the baseline is 4. There are no parameters to document, and the description does not need to add parameter details.

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 transformation: taking a raw capability and producing a fixed-scope, priced, machine-readable commercial offer. This is a clear verb+resource and is distinct from all sibling tools (audit, attest, notarize, etc.), so an agent can identify its purpose without inspecting the schema.

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?

No explicit guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. The sentence implies usage but does not state conditions or route to other tools.

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?

No annotations are provided, so the description carries the full behavioral disclosure burden. It states what is ranked and by which metrics, but does not say whether the operation is read-only, whether it mutates state, what permissions are needed, how errors are handled, or what the return format is.

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 a single front-loaded sentence with no filler, which makes it easy to parse. It is highly compact, though 'candidate money/leads' and 'toward a target' could have been made slightly more concrete without losing brevity.

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, no output schema, and an empty input schema, the description must carry nearly all context. It omits what data source is ranked, how the target is supplied, what the output contains, and any operational constraints, leaving the agent under-informed.

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 defined parameters, so by the scoring baseline this dimension starts at 4. The description does not add meaning for the open additionalProperties input, but with no declared parameters there is limited semantic burden to meet.

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 gives a specific verb, 'Rank,' a specific resource, 'candidate money/leads,' and the ranking criteria, 'euros-per-hour and speed-to-cash toward a target.' It is clear what the tool does, but it does not differentiate itself from related siblings such as audit_opportunity or market_brief.

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 explicit guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The only usage cue is implied by the ranking criteria, leaving the agent to infer the context.

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, the description carries the full behavioral burden. Saying it returns a 'risk score' implies a read-only analysis, but the description never states what the score range means, what input form the message takes, or whether the result includes explanations — all critical for correct invocation.

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?

It is a single front-loaded phrase with no filler, which is efficient. However, it is a sentence fragment rather than a complete statement, and its brevity reflects under-specification rather than disciplined conciseness.

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?

There is no output schema and no annotations, and the description omits how the message is supplied (raw text, ID, object) and how the risk score should be interpreted. For a screening tool with an empty parameter schema, the description leaves too much to inference.

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 declares zero parameters, which per the rubric is baseline 4 since there is no schema-level parameter semantics to compensate for. The open additionalProperties schema is not clarified, but there are no named arguments to document.

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 names a specific resource (a message) and a specific output (phishing/social-engineering risk score), so the agent knows exactly what the tool produces. It does not need sibling differentiation here because none of the sibling tools (clean_csv, endpoint_safety, verify_text, etc.) overlap with this phishing-scoring function.

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 invoke this tool versus alternatives such as verify_text or honesty_audit, which an agent could plausibly confuse with message screening. No preconditions or exclusions are stated.

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, the description must carry the full behavioral burden. It discloses a 24-hour renewable lifetime and a signed receipt, but omits critical traits such as required authentication, side effects, and whether the tool modifies state. This is insufficient for a trust-related operation.

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 a single sentence and avoids fluff, but it packs multiple concepts ('identity surfaces, schema availability and drift') into a dense phrase that is not front-loaded with the tool's action. It is concise but not optimally structured for quick comprehension.

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 zero parameters and no output schema, the description should fully explain what the tool does and returns. Instead, it leaves the core operation ambiguous and does not describe the structure or content of the trust passport, making it inadequate for correct invocation.

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 accepts no parameters, so the empty schema is fully covered. The baseline score of 4 applies because there are no parameter semantics for the description to clarify.

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 names a specific artifact ('24-hour renewable trust passport') and enumerates the surfaces it covers, but never states the action the tool performs (issue, renew, verify) or how it differs from siblings like notarize or attest_quality. An agent cannot tell whether this is a getter or a mutator from the description alone.

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 invoke this tool, what prerequisites exist, or which sibling tools it should be preferred over. The description offers only a static definition, leaving the agent to infer usage from the name alone.

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?

No annotations are provided, so the description carries the full burden. 'Deterministic' is a useful hint about reproducibility, but the description never says what it returns (pass/fail? report?), whether it needs specific input formatting, or what happens on failure. It also doesn't clarify how a deliverable and a spec are supplied when the schema declares no properties.

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?

A single front-loaded sentence that names the operation, the determinism trait, and the four check dimensions with no filler. It is efficient, though the parenthetical list slightly crowds the core statement.

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 definition should say more about return values and the relationship between this tool and the sibling quality/audit tools. As written, an agent can guess the purpose but not predict the response or the required invocation shape.

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 is an empty object with additionalProperties=true, yet the description implies two inputs (a deliverable and a spec) that are nowhere represented or documented. The parameter surface is therefore left ambiguous despite the nominal zero-parameter baseline.

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 clear verb+resource: a deterministic quality check of a deliverable against a spec, and it enumerates the check dimensions (length, coverage, honesty, structure). It does not, however, distinguish this from sibling tools like attest_quality or honesty_audit, which sound closely related.

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 use this tool versus attest_quality, honesty_audit, or audit_opportunity. The agent is left to infer the routing from names alone, and no prerequisites or exclusions are stated.

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