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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds value by explicitly stating it never attests, echoes values, or persists the receipt, clarifying the tool's side-effect-free nature and its limited output (field presence only). This supplements the annotation coverage without contradiction.

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. It states the primary action first ('Check receipt field presence only') and follows with concise constraints. Every word serves a purpose, with no fluff or unnecessary detail.

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 simplicity and the rich parameter schema, the description is mostly complete. The receipt schema explicitly notes that only field names are returned, which covers return semantics. The description itself doesn't explicitly state the output format, but combined with the schema it is sufficient for an agent to know what to expect. A slight gap is not describing potential error conditions or edge cases, but these are minor for a read-only check.

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 parameters have descriptions). The description does not add any parameter-level detail beyond what the schema already provides. For example, the receipt parameter schema already states 'only its field names are returned', and the uri is described as the URI of the attested computation. The description adds no further semantics, so a 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 the tool's purpose: 'Check receipt field presence only' – a specific verb, resource, and scope. It also defines boundaries with 'never attest, echo values, or persist the receipt', which distinguishes it from sibling tools like prepare_attested_computation or inspect_attested_computation that likely perform those operations.

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 negative usage guidance: never attest, echo values, or persist. This implies that if an agent needs those operations, it should use a different tool. While it doesn't explicitly name alternatives or specify exact conditions such as 'use only when you need to verify presence', the constraints are informative enough to route an agent correctly.

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 annotations already disclose readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that it is 'without creating proposals or writes', which reinforces the read-only nature but adds little beyond the annotations. The phrase 'safe staged' hints at the analysis nature but does not explain what the tool checks or returns. Given the strong annotations, the description provides only marginal additional 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?

The description is a single, tight sentence with no filler. It front-loads the primary purpose ('Analyze a local or remote bundle...') and immediately follows with the behavioral constraint ('without creating proposals or writes'). Every word contributes to the agent's understanding 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 read-only analysis tool with comprehensive annotations and fully described parameters, the description is sufficiently complete. It states the tool's purpose, scope, and a critical constraint. One could argue it lacks details on what constitutes 'safe migration' or what the output looks like, but given the absence of an output schema and the tool's specific niche, the description provides enough for an agent to invoke it correctly. The mention of 'staged' hints at workflow context.

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 covers all parameters with descriptions (100% coverage), so the baseline is 3. The description adds meaningful context by specifying that the bundle can be 'local or remote', which is not present in the schema's 'Bundle id to analyze'. This clarifies scope for the agent. For actorMappings and generatedPaths, the description adds nothing beyond the schema, but the bundle clarification justifies a slightly above-baseline score.

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 ('Analyze') and resource ('local or remote bundle') with a specific goal ('safe staged OKF v0.2 migration'). It also includes a strong differentiator ('without creating proposals or writes') that distinguishes it from sibling tools like validate_bundle or okf_list_proposals. This leaves no ambiguity about the tool's 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?

The description implicitly tells the agent when to use this tool: when checking migration safety for a bundle. It also clarifies that it performs no writes or proposals, which is a key usage constraint. However, it does not explicitly name alternatives or state when not to use it, leaving some room for inference. Still, the context is clear enough for correct selection.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that it renders the 'current OKF graph', which is useful context but does not disclose additional behavioral traits such as default limits (available in schema) or output size implications. With annotations covering the safety profile, this is adequate but not rich.

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 immediately states the tool's purpose and the accepted formats. There is zero filler; every word earns its place. It is concise and well-structured for an agent to quickly parse.

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 that the tool is a read-only export with well-documented parameters in the schema, the description is fairly complete for an agent to invoke it correctly. It could optionally mention that the output is plain text/string, but the absence of an output schema and the simplicity of the operation make this a minor gap. The 'current OKF graph' phrasing clarifies scope, and the format enum covers the output variants.

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 every parameter (format, maxEdges, maxNodes, edgeKinds, includeAssets, includeExternal) is already documented in the schema. The description does not add any additional meaning beyond what the schema provides, so the baseline of 3 applies. It does not compensate for any gaps because there are none.

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 specific action 'Render the current OKF graph' followed by the three output formats (JSON, Graphviz DOT, Mermaid text). This distinguishes it from sibling tools like get_graph (which likely returns a structured object) and graph_summary (which summarizes rather than renders). The verb+resource pattern is precise and 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 implies usage for exporting graph data in serialized text formats, but it does not explicitly say when to prefer this over alternatives such as get_graph or get_subgraph, nor does it mention any exclusions or conditions. An agent would need to infer from format options that this is the export tool, but no explicit guidance is given.

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, covering the safety profile. The description adds minimal behavioral context beyond repeating the action ('find') and the bounded constraint, which is also reflected in the maxPaths parameter. It doesn't disclose return format, pagination, or any edge cases, but given the strong annotation coverage, the additional value is limited but not contradictory.

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, concise sentence that front-loads the core action and resource. It is efficient and avoids redundancy, though it could potentially include a brief mention of return behavior without much added length. Still, it is appropriately sized for a tool with a well-documented 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?

Given the tool's complexity (4 parameters, no output schema), the description provides the essential purpose but omits what the return structure looks like (e.g., a list of paths with nodes/edges). The absence of an output schema places some burden on the description to describe the result format, which it does not do. However, the schema covers all input parameters, and the description is adequate for an agent to understand the primary use case without being 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 description coverage is 100%, so all four parameters have descriptive text in the schema. The tool description adds no extra parameter semantics beyond what the schema already provides. For example, 'source' and 'target' are clearly described in the schema, and 'bounded' in the description is only a high-level echo of the maxPaths and edgeKinds parameters. The baseline of 3 is appropriate since the schema handles the documentation burden.

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 ('find'), a clear resource ('relationship paths'), and defines the scope ('between two OKF concepts'). It clearly distinguishes itself from sibling tools like get_neighbors (which returns immediate connections) and get_subgraph (which returns a subgraph) by specifying the path-finding intent and bounded nature. The phrase 'bounded' signals limits, which is further detailed in the schema parameters.

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 implies usage for when you need a path between two specific concepts, but it does not explicitly state when to use this tool versus alternatives like get_neighbors or get_graph. No exclusions or conditions are given for when a different tool would be more appropriate. The context is clear enough for a basic recommendation, but lacks explicit routing 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 readOnlyHint=true and idempotentHint=true, so the description doesn't need to restate safety. It adds value by specifying the exact content returned (frontmatter, Markdown body, links) beyond 'read'. This is useful context, and it does not contradict any annotation.

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 sentence that conveys the action, scope, and content, front-loaded with the verb and resource. 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?

For a simple read operation with an output schema absent, the description adequately covers what is returned. It notes 'valid' which may imply validation behavior, but does not elaborate on error cases. Given the sibling set and the annotations covering safety, nothing critical is missing 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%, so all four parameters (id, uri, path, bundle) are already documented with their roles. The description does not add parameter-specific details beyond what the schema provides, which is acceptable but not exceptional. Baseline 3 applies when the schema 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 clearly states the action ('Read one valid OKF concept') and specifies the resource and its contents (frontmatter, Markdown body, links). It distinguishes itself from sibling tools like list_concepts (browsing multiple) and search_concepts (searching) by being explicitly for a single concept.

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 context for use: retrieving a single concept by its identifier. It does not explicitly mention alternatives or when not to use it, but the 'one' vs. 'list/search' semantics in sibling names imply the usage. No exclusions are stated, but the purpose is 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, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the behavioral trait of being 'bounded,' which is also supported by the maxNodes/maxEdges parameters, but it does not elaborate on default behavior or return format. Given the annotations, the description adds marginal but non-contradictory context; a score of 3 reflects this minimal incremental value.

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, tightly worded sentence with no filler. It front-loads the core purpose ('Return a bounded set of OKF graph nodes and edges') and appends the filtering capability succinctly. Every word earns its place, and the structure is ideal for quick agent 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?

Given the tool's complexity (9 optional parameters) and the presence of many graph-related siblings (get_subgraph, graph_summary, find_paths), the description is minimal. It does not explain what an OKF graph is, how this tool differs from siblings, or what the output looks like (no output schema). While annotations cover safety, the description lacks guidance on when to invoke this tool, leaving agents to infer from parameter schemas alone. This is adequate but not complete for a tool of this scope.

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 each of the 9 parameters has a detailed description. The tool-level description adds no parameter-specific information beyond the generic 'optional concept filters,' which is already implied by the parameter descriptions. With high schema coverage, the baseline of 3 is appropriate; the description does not need to compensate and does not.

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 action ('Return') and resource ('OKF graph nodes and edges') with a scoping qualifier ('bounded set') and optional filters. It is specific enough to convey what the tool produces, but it does not explicitly differentiate from sibling tools like get_subgraph or graph_summary, which also deal with graph subsets. The phrase 'bounded set' and 'concept filters' hints at distinguishing use cases, but the differentiation is implicit.

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 no guidance on when to use this tool versus its siblings. It does not mention alternatives, exclusions, or prerequisites. The only contextual hint is 'optional concept filters,' which suggests it is for filtered graph retrieval, but it does not compare against get_subgraph, find_paths, or graph_summary. An agent would have no basis to choose this over related tools without deeper inference.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no further behavioral context (e.g., return format, pagination, or edge-case behavior). It does not contradict annotations, so a 3 reflects adequate coverage with annotations doing the heavy lifting.

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, concise sentence that immediately states the core purpose. It is front-loaded and contains no extraneous information, earning a perfect score for clarity and efficiency.

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 read-only tool with a clear schema and annotations, the description sufficiently explains what the tool returns. It does not specify output schema, but none is provided, and the nature of 'incoming and outgoing graph relationships' is likely understandable. Minor gaps (e.g., error conditions) are not critical given the tool's simplicity.

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%, meaning every parameter is documented in the input schema. The description gives high-level context (incoming/outgoing relationships) that aligns with the 'uri' parameter, but it adds no extra meaning beyond the schema. The baseline of 3 is appropriate since the schema carries full parameter documentation.

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 ('Return') and a specific resource ('graph relationships for one OKF concept'). It clearly defines the scope (incoming/outgoing relationships) and distinguishes it from siblings like get_graph (full graph) or get_subgraph (subgraph extraction), though it does not explicitly name alternatives.

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 no guidance on when to use this tool versus other graph-related siblings such as find_paths, get_graph, or get_subgraph. It does not state when this tool is preferred or mention any exclusions or prerequisites.

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, idempotentHint=true, and openWorldHint=false, covering safety and predictability. The description adds useful behavioral context—it traces only internal provenance and explicitly avoids fetching external resources—which is a meaningful constraint beyond the annotations. This extra disclosure justifies a score above the baseline.

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 zero waste. It states the action, the subject, and a key constraint efficiently, making it easy for an agent to parse quickly.

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 bears responsibility for indicating what the tool returns. The current text focuses on the process (tracing) but does not describe the shape or format of the provenance result. Given the tool's potential complexity (depth, nodes, external leaves), this is a notable gap, though the description is otherwise adequate for a read-only 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?

Schema description coverage is 100%, so every parameter (uri, maxDepth, maxNodes, includeExternal) is already documented in the schema. The tool description does not add any parameter-specific meaning beyond what the schema provides, so the baseline score of 3 applies.

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 ('Trace') and identifies the resource ('normalized source provenance') with a clear scope ('through internal concepts'). It distinguishes itself by noting 'without fetching external resources', which separates it from tools like read_git_source, though it doesn't name a specific sibling.

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 implies usage context by stating 'internal concepts' and 'without fetching external resources', which hints at when this tool is appropriate (e.g., wanting provenance without external data). However, it does not explicitly name alternative tools or provide exclusion criteria, leaving the agent to infer routing from the sibling list.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the key 'bounded' constraint, which is useful context. However, it does not describe the return format (e.g., whether it returns nodes, edges, or a complete subgraph) or any pagination/limits beyond what the schema provides, which would be helpful for a traversal tool.

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 communicates the core purpose and the key 'bounded' trait. There is no fluff or redundancy; it earns its place entirely.

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 tool with 5 parameters, full schema coverage, and safety annotations, the description is adequate but not complete. It does not clarify what the output looks like (no output schema) nor give any guidance on selecting it over siblings. The 'bounded' term hints at limits, but the schema already covers depth and maxNodes. Additional context about result structure or typical use cases would improve completeness.

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 fully documents all five parameters (uri, seeds, depth, maxNodes, edgeKinds). The description does not add meaning beyond the schema—it only implies traversal from seeds. With full coverage, the baseline of 3 is appropriate; the description adds minimal extra value.

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 the specific action 'Traverse' and the resource 'bounded OKF subgraph' with a clear mechanism 'outward from seed concepts'. It is distinct enough from siblings like get_neighbors and find_paths, though it does not explicitly name alternatives. The verb and scope are clear.

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 no guidance on when to use this tool versus alternatives such as get_neighbors, find_paths, or get_graph. It does not mention any exclusions or conditions that would select this tool. The existence of multiple graph-traversal siblings makes this a significant gap.

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 provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds minimal extra behavioral context—it does not mention performance, data freshness, or any side effects. Since annotations are present, the bar is lower, but the description still adds no additional insight beyond what annotations already 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 a single, concise sentence with no filler. The verb 'summarize' is front-loaded, and the list of covered entities is clear and complete.

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 simplicity (no parameters, no output schema, clear annotations), the description fully conveys what the tool does and what to expect (counts). No critical information is missing for an agent to invoke 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 tool has zero parameters, and the schema is empty with 100% coverage. The description doesn't need to explain parameter semantics, so the baseline of 4 applies. It correctly implies that no input is required.

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 action (summarize) and the resources covered (bundle, concept, edge, type, tag, graph health counts). It distinguishes itself from sibling list/get tools by focusing on aggregated counts rather than individual data retrieval.

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 implies use when an overall summary of counts is needed, but it does not explicitly state when to prefer this over sibling tools like get_graph or list_*. No exclusions or alternatives are mentioned, leaving some ambiguity for the agent.

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 cover safety (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the description does not need to repeat that. It adds useful context about inspecting 'indexed inert artifacts' and reinforces the non-execution guarantee, which is consistent with annotations and adds value beyond them.

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, efficient sentence that front-loads the primary purpose and the key limitation ('never execute it'). No redundant phrases or unnecessary elaboration.

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 clearly states the purpose and limitation, and the parameter schema is complete, but with no output schema it leaves the return format unspecified. For a read-only inspection tool, this is a minor gap, but the description could hint at what the agent will receive (e.g., static analysis details). It is adequate but 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?

The input schema provides descriptions for all 4 parameters (100% coverage), so the description does not need to add parameter-level details. The description is tool-level and adds no extra meaning about individual parameters, matching the baseline for high coverage.

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 ('statically inspect') and a specific resource ('Attested Computation contract and indexed inert artifacts'), and explicitly excludes execution ('never execute it'). This clearly differentiates it from sibling tools like prepare_attested_computation and check_computation_receipt without needing to open their schemas.

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 context (static inspection, non-execution) and an explicit exclusion ('never execute it'), but it does not name alternative tools or specific conditions for when to choose this tool over others. The exclusion gives some when-not guidance, but there is no explicit reference to alternatives.

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, so the safety profile is covered. The description adds useful context beyond the schema by specifying 'loaded by the server', which clarifies the data source. However, it doesn't disclose return format, ordering, or potential performance implications. Given the low bar set by annotations, a 3 is appropriate – it adds moderate value without describing full 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?

The description is a single, tightly worded sentence that conveys the entire purpose without any filler. It front-loads the verb and resource, and every word earns its place. No redundancy or unnecessary detail.

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 no-parameter list tool with annotations covering safety and idempotency, the description is fully adequate. It clearly states what is listed (local and remote bundles) and the condition (loaded by the server). With no output schema required, nothing essential is missing for an agent to invoke 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?

With zero parameters and the schema being empty, there is nothing for the description to add about parameter semantics. Per the rubric, a baseline of 4 is given for tools with 0 parameters. The description correctly avoids inventing parameters and needs no further clarification.

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 ('List'), a clear resource ('OKF bundles'), and scopes it precisely to 'local and remote' and 'currently loaded by the server'. This differentiates it from the sibling 'list_remote_bundles', which suggests a narrower scope. The purpose is unambiguous and distinguishable from peers.

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 clearly establishes context (local and remote bundles loaded by the server) without explicitly naming alternatives or when-not-to-use scenarios. It would benefit from a pointer to 'list_remote_bundles' for remote-only queries, but the absence of that doesn't mislead; the scope is self-evident. No exclusions are needed for a simple listing 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds minimal behavioral context beyond what annotations provide, such as the fact that results are compact summaries, but it does not disclose pagination behavior or any edge cases. Given the baseline from annotations, a 3 is appropriate.

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, tightly written sentence with no filler words. It front-loads the core purpose and then lists the optional filters, achieving maximum clarity with minimal text.

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 is adequate for a list tool with fully documented schemas and annotations, but it does not state pagination behavior, sorting, or any error cases. Given the 7 parameters and absence of an output schema, a slightly richer description could help, but the current one is sufficient for an agent familiar with the schema. A 3 reflects this balance.

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 all 7 parameters are already documented in the schema. The description only summarizes these filters without adding new semantics or syntax details. Since the schema handles the heavy lifting, the description adds no significant value beyond what is structured, aligning with the baseline of 3.

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 action (List) and resource (OKF concept summaries) and mentions the available filters. It is clear and distinct, though it does not explicitly differentiate from siblings like search_concepts or get_concept, but the purpose is self-evident.

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 implies usage through the filters (bundle, type, tag, text), but it does not explicitly state when to use this tool versus alternatives such as search_concepts or get_concept. There is no mention of exclusions or preferred conditions, leaving the agent to infer usage from the filter list.

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, idempotentHint: true, and destructiveHint: false, so the safety profile is covered. The description adds 'current graph' scoping and the distinction between standard and extension kinds, which provides some context. However, it does not disclose return format, error conditions, or performance implications—though these are less critical given the strong annotations. Overall, it adds limited behavioral insight beyond the 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 a single, directly actionable sentence with no filler. It front-loads the verb and resource, and every word contributes to meaning. It is optimally concise.

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?

Since there is no output schema, the description carries the burden of explaining the result. It only says 'Count' without specifying the return format (e.g., a list, map, or aggregate). Furthermore, terms like 'standard semantic' and 'extension' are left undefined, which could be ambiguous to an agent without domain context. For a parameterless read-only tool, this is a moderate gap in completeness.

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, so the baseline is 4. With no parameters, the description has no need to clarify parameter semantics; the schema is trivially complete. Nothing is missing in this dimension.

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 action ('Count') and the resource ('standard semantic and extension edge kinds') scoped to the current graph. It is specific enough to distinguish from sibling list tools like list_types or list_relation_types, though it does not explicitly name them. The purpose is unambiguous and not a tautology.

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 alternatives. It does not mention excluded cases, prerequisites, or favorable contexts. Since sibling tools have overlapping list functions, the absence of any usage direction leaves the agent to infer applicability.

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 carry the safety profile (readOnlyHint, idempotentHint, destructiveHint), lowering the bar. The description adds the 'current OKF graph' scoping context, which is useful. It does not disclose the return shape (an integer count vs a breakdown by type) or how the graph snapshot is established, so it adds only modest value beyond the 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?

A single, two-clause sentence with the operative verb front-loaded. No filler, no redundant restatement of the name, and every word earns its place.

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?

Adequate for a zero-parameter read tool, but the phrase 'typed relations' is left undefined and there is no output schema to clarify the return value. The possible conflation with list_edge_kinds and the unspecified result format leave an agent with minor ambiguity. Given the tool's simplicity and the strong annotation coverage, this is acceptable but not thorough.

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, and schema coverage is trivially 100%, so there is nothing for the description to document. Per the baseline for zero-parameter tools, a 4 is appropriate; no parametric detail is missing or expected.

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?

Clear verb ('count') and resource ('typed relations'), scoped to the 'current OKF graph'. The action is concrete and an agent can tell this counts rather than lists. It does not explicitly differentiate from the sibling list_edge_kinds, with which 'typed relations' could plausibly overlap, 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?

No guidance on when to use this tool versus the siblings. With list_edge_kinds, list_types, and get_graph nearby, an agent has no hint about which to prefer for enumerating relations vs counting them, or whether list_edge_kinds is the richer alternative. This is a real gap.

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, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds useful behavior: 'metadata' implies it returns metadata rather than content, and 'currently loaded' indicates a snapshot of the server's state. It doesn't discuss pagination or ordering, but given the annotation coverage, this is adequate; the description provides some value beyond the 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?

A single, front-loaded sentence that states exactly what the tool does with no redundant wording. Every word serves a purpose, making it highly efficient and easy to parse.

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 parameterless, read-only list tool with annotations covering safety, the description is complete. It specifies what is returned (metadata), the scope (remote bundles), and the state (currently loaded). No critical information is missing for this level of complexity.

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, so the schema is trivially 100% covered. There is nothing for the description to add about parameters, and it makes no misleading claims. The baseline for 0 parameters is 4, which is appropriate 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 clearly states the verb 'List', the resource 'remote bundles', and adds the qualifier 'currently loaded into the server', which distinguishes it from the sibling 'list_bundles' (likely local bundles). The purpose is unambiguous and specific.

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 about when to use it: when you need metadata for remote bundles that are loaded. However, it does not explicitly mention when not to use it or name alternatives like 'list_bundles', though the word 'remote' implicitly differentiates. This is clear context without explicit exclusions, fitting the 'clear context, no exclusions' level.

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, covering the safety profile. The description adds the scope context ('current OKF index') but does not disclose other behavioral traits such as return format, performance expectations, or any side effects beyond what annotations already imply. This is a minimal but non-contradictory addition.

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. It states the action and scope immediately, making it efficient and easy to parse.

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 tool with no parameters and no output schema, the description is mostly complete. It clearly states what is counted and the scope. The only minor gap is the lack of explicit description of the return value shape (e.g., list of tag counts), but this is likely inferable given the simplicity.

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, so the description carries no parameter burden. The baseline for zero parameters is 4, and the description adds no unnecessary detail, leaving the schema fully sufficient.

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 ('Count') and a precise resource ('tags present on concepts in the current OKF index'), which clearly distinguishes it from sibling tools like list_types or list_concepts. The scope is unambiguous and the action is well-defined.

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 guidance is provided on when to use this tool versus alternatives. There is no mention of exclusions, prerequisites, or conditions that would favor this tool over its siblings. The intended context is only implied by the description's focus on counting tags, but no explicit routing is given.

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, so the safety profile is covered. The description adds minimal behavioral disclosure beyond stating it returns a count, which is consistent with the name's mismatch (list vs. count). No contradiction, but no extra context like performance or return shape beyond 'count'.

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, straightforward sentence that immediately conveys the operation. There is no fluff, and the key information is front-loaded.

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 parameterless read-only tool, the description provides enough context to understand what the tool does and what it returns (a count). It doesn't explicitly state that it returns a numeric count rather than a list, but the verb 'count' implies it. Given annotations cover safety and no input is needed, this is sufficiently 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?

The tool has zero parameters, and schema coverage is 100% (effectively, since there is nothing to describe). Per the baseline for 0 params, a score of 4 is appropriate because no parameter documentation 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 uses a specific verb ('Count') and identifies the resource ('concept types present in the current OKF index'). It clearly distinguishes from siblings like list_concepts (which lists concepts themselves) and list_tags (which lists tags), establishing a unique 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 implies a read-only count operation, but no explicit guidance is given about when to use this vs. similar tools like list_concepts or list_relation_types. With many list_* siblings, a brief mention of alternatives or exclusions would improve this dimension.

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 and idempotentHint=true, and the description is consistent with these. The description adds value by specifying that the response includes candidate content and a validation result, which is useful behavioral context beyond the safety profile. No contradictions found.

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 states the action and key details without redundancy. Every word earns its place, and no filler exists.

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 appropriately outlines what the response includes (candidate content and validation result). The tool is simple (one parameter, read-only, idempotent), and nothing critical is missing for correct invocation. It could mention error cases, but that is not required for this simple read 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 input schema fully describes the single parameter (proposalId) with its origin ('Identifier returned when the proposal was created'), achieving 100% coverage. The tool description does not add further parameter details, but the schema alone is sufficient, so 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 states a specific verb ('Read'), a resource ('one authoring proposal'), and key content ('candidate content and validation result'). This clearly distinguishes it from listing tools like okf_list_proposals and validation tools like okf_validate_concept, making the purpose 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 implies single-item retrieval via 'one authoring proposal', but it does not explicitly name alternatives or state when to use this tool instead of others. The 'one' provides clear context, but exclusions or comparisons are absent, leaving guidance to inference rather than explicit direction.

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, idempotentHint=true, and destructiveHint=false, covering safety. The description adds that it returns 'compact metadata', which gives some insight into output format, but doesn't elaborate on behavior or side effects. Given annotations carry most of the burden, this is adequate but not rich.

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 wasted words. It states the action and resource immediately and includes a qualifier about the return type. Perfectly concise.

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 tool is simple: list with optional filters. Annotations cover the read-only, idempotent nature, schema covers the parameters, and the description hints at the output being 'compact metadata'. It lacks explicit mention of pagination or ordering, but these are likely not critical for such a listing tool. Overall, it's reasonably 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?

Both parameters are fully described in the input schema (100% coverage), so the schema already documents them. The description adds no additional parameter-level details, so it meets the baseline for a schema-covered 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?

The description states 'List compact metadata for stored authoring proposals,' which clearly identifies the action (List) and resource (authoring proposals), and adds 'compact metadata' to hint at return format. It is distinct from sibling 'okf_get_proposal' by being plural, though it doesn't explicitly differentiate itself, so it's not a perfect 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?

No guidance on when to use this tool versus alternatives like okf_get_proposal or other list tools. The description doesn't mention conditions, exclusions, or prerequisites, leaving the agent to infer usage 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?

Annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true) already establish the safe, non-destructive nature. The description adds the word 'safe', which is not explained further, but it does not contradict annotations. Minimal additional behavioral context is provided beyond what annotations already 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 a single, efficient sentence that directly states the tool's function. No filler, no redundancy, and the core action is front-loaded. It is an excellent example of concise specification.

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 utility tool with four well-documented parameters and no output schema, the description adequately conveys what it does. It implies that the tool returns a path (since it 'suggests' one), and the 'safe' qualifier hints at validation. Given the low complexity, it is sufficient 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?

Schema description coverage is 100%, so every parameter already has a clear description. The tool description does not add any additional meaning to the parameters, such as constraints, format expectations, or relationships. The schema does the heavy lifting; the description simply restates the purpose without enriching parameter semantics.

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 ('Suggest') and resource ('bundle relative Markdown path'), and specifies the inputs ('from a concept type and title'). This clearly distinguishes it from siblings like find_paths (which deals with graph paths) and list_bundles (which deals with bundle listing). No ambiguity about what the tool produces.

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 alternatives, nor any conditions or prerequisites. It simply states what it does without contextualizing its use within the broader workflow. An agent would have to infer that this is a path construction helper, not something to be used for searching or listing.

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, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the explicit detail that it does not write a proposal or concept file, which reinforces the non-destructive behavior. However, it does not disclose what the validation returns (e.g., success/failure, error list), so the description provides only marginal value beyond the 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 a single, concise sentence with no filler. The key constraint ('without writing a proposal or concept file') is front-loaded, making it immediately clear what the tool does not do. This is an appropriate size for a validation tool with few parameters.

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 should explain what the tool returns (e.g., validation result, errors) but does not. It also gives no details about what 'validate' entails (e.g., required frontmatter fields, path rules). Given the tool's moderate complexity (nested frontmatter object, multiple parameters), this description is too sparse for an agent to fully understand the tool's behavior without probing.

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%, meaning every parameter (path, frontmatter, body, bundle) is already described in the input schema. The description adds no additional meaning about parameter semantics, such as required combinations or validation rules, so it relies entirely on the schema, matching the baseline of 3.

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 ('Validate') and resource ('a proposed new OKF concept'), and adds the key delimiting phrase 'without writing a proposal or concept file' which clearly distinguishes it from write-oriented tools and aligns with its read-only nature. This is not a tautology and differentiates it from sibling validation tools like validate_bundle and validate_project by targeting a concept-level 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 implies that the tool is for validating a concept before writing any files, but it does not explicitly state when to use it versus alternatives such as validate_bundle or validate_project. No exclusions or alternative tool names are mentioned, leaving the agent to infer the appropriate context from the tool name and the 'without writing' phrase.

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, idempotentHint=true, and destructiveHint=false. The description adds value beyond these by stating that the tool does not execute the computation ('non-executing') and does not echo parameter values, which has privacy/security implications. It also implies validation ('Check declared parameters'), though it does not explicitly describe error behavior. No contradiction exists between description and 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 a single sentence that is entirely functional: it states the action, the object, the output, and a critical behavioral constraint. It is front-loaded with the primary action and has zero unnecessary words. This is exemplary 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?

With no output schema, the description should explain what the tool returns. It mentions 'produce non-executing digests' but does not specify the digest format, whether a receipt or error is returned, or what 'declared parameters' implies beyond the schema. Given the tool's role in attested computations and the availability of sibling tools like check_computation_receipt, the lack of explicit output details leaves some ambiguity for an agent deciding how to use the result.

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%: 'uri' is described as 'Canonical or compatibility URI of the Attested Computation.', 'asOf' as 'UTC ISO date or datetime for freshness evaluation.', and 'parameters' as 'Parameter values keyed only by declared names.' The description adds no additional meaning beyond these, so the baseline of 3 is appropriate. It does not clarify formats or edge cases beyond the schema's descriptions.

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 action ('Check declared parameters and produce non-executing digests') and the resource ('Attested Computation'), and adds a critical constraint ('without echoing parameter values'). This distinguishes it from siblings like inspect_attested_computation (which inspects existing computations) and check_computation_receipt (which checks receipts). The verb 'produce' and the specific output 'digests' make the tool's function 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?

There is no guidance on when to use this tool versus its siblings. It does not mention prerequisites (e.g., whether the URI must reference an existing computation), nor does it suggest a workflow context (e.g., 'use this before submitting for verification'). The description only states what it does, leaving the agent to infer appropriate usage from the name and sibling 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is established. The description adds value by disclosing 'digest verification' (integrity checking) and 'byte bounds' (content size limit), which are behavioral traits beyond the annotations and potentially affect call outcomes (e.g., failures or truncation).

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 sentence packs the action, scope, and key constraints without waste. The critical qualifiers are front-loaded, making the tool's intent immediately clear. No redundant or filler text.

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 read-only tool with no output schema and simple parameters, the description conveys the essential constraints (reference requirement, digest verification, byte limits). It could mention the return format, but the lack of output schema and the simplicity of the operation make the current description adequate. The qualifiers about 'already indexed' are useful context.

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, so the schema already documents each parameter's meaning. The description does not add parameter-specific detail beyond referencing 'byte bounds' which maps to maxContentBytes; it meets the baseline but does not go further.

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 ('Read') with a precise resource ('bundle asset') and adds distinguishing qualifiers ('explicitly referenced, already indexed') plus operational details ('digest verification and byte bounds'). This clearly differentiates it from generic read tools and sibling operations like read_git_source.

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 'explicitly referenced, already indexed' implicitly tells the agent the asset must be known by URI or bundle+path, steering toward use when a specific asset is targeted. It does not explicitly name alternatives or exclusions, but the context is clear enough for a read operation within a known bundle.

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 annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the key behavioral detail 'without fetching' and the prerequisite 'explicitly mapped', which are not present in annotations. No contradiction exists; the description enriches the safety profile with operational 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?

The description is a single, compact sentence that front-loads the action ('Read') and states the core constraints without any filler. Every word carries meaning, making it ideal for quick agent 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?

For a simple read operation with three parameters and no output schema, the description adequately covers purpose, constraints, and the 'without fetching' behavior. It lacks explicit return format details and error conditions, but given the simplicity and the presence of safety annotations, the agent has sufficient information to decide when to call and what to expect.

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 provides complete descriptions for all three parameters (concept, sourceId, maxContentBytes), achieving 100% coverage. The tool description mentions 'pinned sources[].git entry' and 'explicitly mapped checkout', which loosely map to concept and sourceId, but it does not add new syntax or format details beyond the schema. Baseline of 3 applies.

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 ('Read'), a precise resource ('one pinned sources[].git entry'), and a scope ('from an explicitly mapped checkout or bare repository'). It also distinguishes the tool by its 'without fetching' behavior, clearly separating it from potentially similar read operations like read_bundle_asset.

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 context on when to use the tool: for a pinned git entry in an explicitly mapped checkout or bare repository, and explicitly states 'without fetching' as a behavior. It implies that if the source is not pinned or not explicitly mapped, or if fetching is desired, another tool should be used, though it does not name alternative tools explicitly.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered structurally. The description adds the 'ranked summaries' output nature, which is genuinely useful context. It does not, however, disclose pagination, the temporal significance of the asOf parameter, or result-shape variation across the detail enum — modest gaps that annotations do not cover.

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 sentence, front-loaded with the imperative verb 'Search,' that packs the verb, resource, output nature, and filter modes with zero filler words. Nothing is wasted and nothing is repeated from the schema or annotations.

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 tool with 23 parameters and semantics like temporal asOf, freshness states, trust tiers, and frontmatter object filters, a one-line description is thin on orienting context. However, the schema fully documents every parameter and the annotations cover the safety profile, so the agent can still invoke it correctly. 'Ranked summaries' hints at output, and no output schema exists to carry the return contract.

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% — all 23 parameters carry their own descriptions in the schema, including the detail enum, offset/limit ranges, and filter semantics. The description adds zero parameter-level detail beyond the schema, which is the correct baseline (3) for a fully self-documenting 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?

The description names a specific verb ('Search'), a resource ('OKF concepts'), and an output shape ('return ranked summaries'), with the scope delimited by 'using text and structured filters.' This clearly distinguishes a search-and-filter operation from the sibling list_concepts (pure enumeration) and get_concept (single retrieval). It loses a point only because it never names or explicitly contrasts those 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 phrase 'using text and structured filters' implies this is the go-to tool when free-text or structured filtering is needed, in contrast to the listing siblings. However, with four list/search-adjacent sibling tools (list_concepts, get_concept, get_neighbors, find_paths), there is no explicit statement of when to prefer this tool over those, nor any exclusion or prerequisite 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?

The description aligns with the annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true), and adds meaningful behavioral detail beyond them: it clarifies that when 'bundle' is provided the validation is isolated to that bundle, and when absent it applies to the full current index. This is a substantive operational nuance not captured in annotations, but it doesn't deepen further (e.g., what the report contains or failure modes), so it stops short of a 5.

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 that leads with the action and resource, then states the scope condition. There is no filler or redundant phrasing; every clause carries necessary information about purpose and selection. It is efficiently front-loaded and easy to parse.

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 tool with one optional parameter, read-only annotations, and no output schema, the description covers the essential aspects: the purpose, the distinction from project validity, and the two invocation scopes. It does not explain domain terms like 'OKF conformance' or describe the output format, but given the simplicity of the tool and the low risk indicated by annotations, it is sufficiently complete for an agent to invoke it correctly. A slight gap is the lack of guidance on output structure, but that is not critical for a report-style tool.

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 documents the single 'bundle' parameter as 'Optional bundle id to validate in isolation,' and the description adds the complementary behavior when the parameter is omitted (full current index). This gives the agent a complete picture of the parameter's semantics, going slightly above the schema baseline of 3. With 100% schema coverage, the description adds the critical default-case logic, warranting a 4.

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 ('Report'), a clear resource (OKF conformance), and explicitly contrasts it with project validity. It also specifies the target scope ('one bundle or the full current index'), which distinguishes it from the sibling validate_project tool. Even without title, the agent can determine what this tool does and how it differs from closely related 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 phrase 'separately from project validity' signals that this tool is appropriate when OKF conformance is the concern, distinct from validate_project. It also clarifies the two operating modes (single bundle vs. entire index), giving the agent a basis for deciding how to call it. However, it does not explicitly state when not to use it or name the alternative tool, relying on the implicit contrast rather than an explicit routing instruction.

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 and idempotentHint, covering safety. The description adds that it reports structured diagnostics and targets the complete configured project, which supplements the annotation context but does not elaborate on output format or edge cases such as partial validity.

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 wasted words. It conveys the core purpose and scope efficiently.

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 should clarify the return value. It mentions 'structured diagnostics' but does not specify the structure, fields, or how errors are represented. Given the tool's simplicity and annotation coverage of safety, the gap is moderate.

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 100% schema coverage (empty schema). The baseline of 4 applies because there is nothing to explain; the description correctly scopes the operation to the entire project.

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 verb 'report' and the resource 'complete configured project', specifying three outcomes: OKF conformance, project validity, and structured diagnostics. It implicitly distinguishes from bundle- or concept-level validators like validate_bundle and okf_validate_concept by focusing on the whole project, though it does not name 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?

No guidance is given on when to use this tool versus the many sibling validation tools (e.g., validate_bundle, okf_validate_concept). The description implies a whole-project scope but does not explicitly state alternatives or when to choose it over them.

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