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

Even with readOnlyHint and idempotentHint annotations, the description adds substantial behavioral detail: the structural detection ladder, legacy adbe.pkcs7.detached handling, normativeBasis 'T3', scope object semantics, cross-reference table reconstruction caveats, truncation behavior, and LTV capping rules. It clarifies exactly how results should be interpreted, which far exceeds what the annotations convey.

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 long but well-organized and front-loaded: purpose first, then the critical observation-versus-verdict caveat, followed by technical details, arguments, return shape, and examples. The Args block is somewhat redundant with the schema, but the density is justified given that there is no output schema and the tool has nuanced interpretation semantics.

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, the description carries the full burden of explaining what the tool returns, and it does so thoroughly: top-level object shape, .levels, levelsTruncated, scope object fields, per-signature evidence, and the LTV cap. It also covers edge cases like reconstructed cross-reference tables, encrypted documents, and legacy signatures, making the tool safely callable and interpretable.

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 covers both parameters with 100% coverage, so the baseline of 3 applies. The description's Args section mostly repeats the schema (absolute path, markdown/json default) and adds little new semantic meaning about the parameters themselves, though it does tie response_format to output behavior like JSON never being length-truncated.

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 opening sentence states a specific action ('Observe which PAdES baseline level...') on a specific resource ('the structure of each signature'), immediately grounding the tool's purpose. It also distinguishes itself from conformance validation by explicitly saying 'This is an observation, not a conformance verdict,' which separates it from siblings like validate_conformance.

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 clear use cases ('Check if a signature is long-term validation (LTV) enabled', 'Audit whether archived contracts meet B-LTA requirements') and strongly warns against treating results as conformance verdicts. It does not explicitly name sibling tools or state 'use X instead', but the observation-versus-verdict framing and examples provide clear contextual guidance.

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?

Annotations already declare readOnly/openWorld/idempotent/non-destructive, and the description adds meaningful behavioral detail: verdicts are deterministic and code-decided, firedRules/advisories are explanatory not overridable, the scope object must be read before the verdict, reconstructed xref tables change the meaning of results, and signature lists can be truncated but JSON is not. No contradiction with annotations.

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 text is long but structured into Purpose, Args, Returns, and Examples, and each section serves a clear need for a tool of this complexity. The core purpose is front-loaded, and the return-value caveats are grouped rather than scattered. No sentence is purely 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?

There is no output schema, so the description correctly takes responsibility for explaining return semantics. It covers the scope object, verdict, firedRules, advisories, truncation behavior, and the reconstructed-table caveat. Given the tool's 18 parameters and complex behavior, nearly everything an agent needs to select and invoke it correctly is present.

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%, and the Args section largely restates the schema's parameter meaning. The description does add some contextual significance, such as trust anchors capping the verdict and revocation freshness affecting 'good' status, but those points are also present in the schema. This is the baseline case where structured data already does the heavy lifting.

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 specific verb and outcome: 'Produce a deterministic 4-value trust verdict... for a PDF.' It also differentiates itself from lower-level siblings by stating that it runs verify_signatures, verify_integrity, and detect_pades_level internally, so the agent knows this is the policy-level aggregation tool, not a raw verifier.

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 examples give concrete use cases (gating invoices, deciding on countersigned contracts, batch-auditing), and the description clarifies it is not a content-truth tool. It names the internal verifiers as components rather than alternatives, but does not explicitly say 'use verify_signatures when you need raw signature details,' so explicit when-not guidance is slightly incomplete.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the description adds valuable context beyond that: it explains the 'scope' object, what chainStop and reconstructed mean, and warns that results over a rebuilt cross-reference table carry different weight. It also mentions encryption handling. This is rich behavioral disclosure not available in annotations.

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 distinct sections (Args, Returns, IMPORTANT, Examples) and is front-loaded with the core purpose. Every section earns its place, providing essential context about output semantics and usage. Despite its length, it remains focused and technically precise 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?

There is no output schema, so the description must explain return values. It does so thoroughly, detailing the scope object, the declared conformance fields, and the PDF version. Examples further clarify expected use. Given the tool's complexity and the absence of an output schema, the description is complete enough 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?

Schema description coverage is 100%, with both file_path and response_format already clearly described, including the enum and default. The description's 'Args' section restates these but doesn't add new meaning beyond the schema. Thus the baseline of 3 applies; no extra semantic value is introduced.

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 (Identify) and resource (declared PDF/A and PDF/UA conformance in XMP metadata), and explicitly distinguishes itself from validate_conformance by noting it only identifies declarations, not actual conformance. This clearly differentiates it from siblings.

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 names the alternative tool (validate_conformance) and the exact condition when to use it instead ('for real PDF/A rule checking'), along with examples of appropriate use cases. This leaves no ambiguity about when to select this tool.

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?

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds substantial behavioral context beyond that: determinism ('Same file plus same given facts always produce the same result'), result-size limits and truncation semantics (200 entries, resultsTruncated), the reconstruction of the cross-reference table and its meaning, the four decision states including needs_external_fact (never defaulted into pass), and the warning that 'A result with no failures is not proof of conformance'. This is far more transparency than annotations alone provide.

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 long but appropriate for the tool's complexity. It is front-loaded with the core purpose, then structured into Args, Returns, and Examples. There is some redundancy (e.g., 'observation' is explained multiple times, and the 'scope' warning appears twice), which slightly dilutes conciseness, but each section earns its place by conveying necessary detail for correct invocation and interpretation.

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 absence of an output schema, the description must carry the full burden of explaining return semantics. It does so thoroughly: public scope object, result states, evidence for failures, context notes, traces, truncation, observation fields, and the conformance caveat. For a tool with nested parameters and complex outcomes, nothing essential for correct use 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 description coverage is 100% for all four parameters, giving a baseline of 3. The description adds meaning beyond that: it explains the 'given' parameter as external facts that can yield needs_external_fact outcomes, contextualizes 'domains' as the bundled set (font-embedding, document-metadata, annotation), and clarifies response_format choices. It does not repeat schema details but enriches them with operational consequences.

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 precise verb ('Check') and resource ('a PDF'), then delimits the scope: constraints mapped from ISO 32000-1/-2 clauses, explicitly excluding PDF/A or PDF/UA. It distinguishes itself from veraPDF and sibling conformance tools by pointing out what it covers that they do not. This gives an agent a clear, non-overlapping purpose.

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 explains when this tool is appropriate: when veraPDF is insufficient (e.g., 'Find out why a viewer warns about a font that veraPDF considers fine') and for going beyond PDF/A profiles before shipping. It names veraPDF as the alternative for profile checks. It does not explicitly enumerate exclusions for every sibling (signatures, integrity, policy), but the scope definition ('not PDF/A or PDF/UA') and examples make the intended use fairly unambiguous.

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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description's job is to add context beyond those. It does extensively: explains the hybrid engine selection (veraPDF vs native), how failures are reported (authoritativeValidation.performed and reason), the exact meaning of the 'scope' object, truncation behavior, severity levels for PDF/UA, and the handling of encrypted PDFs. No contradiction with annotations, and it provides a rich behavioral layer well beyond what annotations convey.

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 long but well-structured: it opens with a purpose statement, then engine details, an Args list, Returns section, a Note on limitations, and Examples. Each sentence carries information and there is no redundant padding. While length is high, it is justified by the tool's complexity; it earns a 4 rather than 5 because the length could be slightly tightened without losing meaning.

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 tool's complexity (hybrid engine, multiple flavours, varied return semantics, and truncation rules), the description is remarkably complete. It explains the return structure ('scope' object, violation list truncation, severity handling), addresses edge cases (encrypted PDFs, missing veraPDF, unreconstructable content streams), and even notes when rules are skipped rather than guessed. With no output schema present, the description carries the full burden of explaining return values, and it does so thoroughly. No important aspect seems missing for an agent to call 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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema: it explains default flavour behavior (PDF/A precedence over PDF/UA, fallback to pdfa-2b), engine 'auto' behavior (delegates to veraPDF when installed), encryption handling for password (decryption before structure checks, empty user password tried automatically), and validation rules lists. This goes beyond the schema's terse field descriptions, justifying one point above 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 clearly states the tool validates PDFs against PDF/A (ISO 19005, archiving) or PDF/UA (ISO 14289, accessibility), giving both the verb and specific resource. It distinguishes itself from likely siblings like identify_conformance (detection) and validate_clauses (different focus) by explicitly focusing on conformance validation.

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 clear context on when to use the tool (checking archive conformance, verifying accessibility before publishing) and provides three concrete examples. It also notes limitations (PDF/UA cannot be fully decided by machine) and directs users to pdf-reader-mcp's inspect_tags for deeper structure examination. However, it does not explicitly contrast with sibling validation tools, so a half-point is lost.

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?

The description goes well beyond the readOnly/idempotent annotations by explaining non-obvious behavior: 'indeterminate' is not a pass, a non-null revisions list may be incomplete, 'unwalkable' means undetermined rather than unchanged, reconstructed cross-reference tables weaken conclusions, and lists can be truncated. It also clarifies that incremental updates are legal and findings are observations, not verdicts. This is exactly the kind of behavioral nuance an agent needs beyond structured annotations.

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 long, the description is dense and well organized: purpose, key outputs, classification rules, limits, argument list, return-scope guidance, and truncation policy. Every section earns its place given the complexity of the tool, and the most decision-critical caveats are emphasized with bold text. It is structured for efficient scanning rather than padded.

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, the description must carry the burden of explaining return semantics, and it does: scope object, revisionChain status values, revisionCountAgreement, violationAssessment values, truncation behavior, and meaningful examples. Given the tool's complexity and the absence of an output schema, nothing critical 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 description coverage is 100%, so the schema already documents both file_path and response_format, including the enum and default. The Args section in the description duplicates that information without adding new semantic constraints. Baseline 3 is appropriate because the description does not need to compensate for schema gaps here.

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 specific verb and resource: "Analyze a PDF for modifications after signing." It clearly distinguishes this tool from signature-validity or conformance checking by focusing on post-signing modifications, revision history, and tamper-relevant observations. The title reinforces this as tamper detection, and the scope is unambiguous.

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 clear context for when the tool is appropriate: checking whether a signed document was modified after signing, and reviewing integrity findings rather than treating them as automatic tampering verdicts. It also explicitly offloads page-geometry questions to pdf-reader-mcp, which helps an agent decide what this tool is not for. It does not explicitly name sibling tools or state 'use X instead' conditions, so it stops just short of a 5.

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?

The description goes far beyond the annotations by disclosing exact verification behavior: digest recomputation, CMS verification, timestamp validation, trust-chain evaluation, revocation modes, scope.reconstructed semantics, response truncation, and validation-time rules. It also clarifies that without trust_anchors, trust is not_evaluated. No annotation contradiction exists.

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 long but well-structured: purpose, Args, Returns, behavioral caveats, alternatives, examples. The front-loaded core sentence and clear headings help an agent locate relevant sections quickly. Some redundancy exists between Args and the input schema descriptions, but the overall organization earns its length for a complex verification 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 output schema, the description explains the return shape in detail, including scope semantics, per-signature status fields, truncation behavior, validation-time selection, and trust-anchor implications. It also covers important edge cases like rebuilt cross-reference tables and revoked certificates. This is complete enough for an agent to call the tool correctly and interpret results.

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%, so the baseline is 3. The description largely restates the schema's parameter descriptions rather than adding substantially new semantics. Some context is added (e.g., trust env var behavior, RFC 6960 reference), but most parameter-meaning is already present in the input schema, so the description does not meaningfully compensate beyond the 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?

Opens with a specific verb and resource: 'Cryptographically verify the digital signatures in a PDF document.' The title reinforces the scope, and the description distinguishes it from structural inspection by naming inspect_signatures, which 'inspects structure only.' The purpose is unambiguous and differentiates the tool's role from the listed siblings.

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 clear usage context through the cryptographic verification steps, the note that inspect_signatures is structural only, and three concrete example use cases (integrity check, trust anchor validation, revocation checking). It does not explicitly enumerate exclusions for every sibling tool, so it stops short of a 5, but the guidance is strong.

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