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

No annotations provided, so description carries full disclosure burden. Successfully conveys prerequisite that files must be 'staged' and operational constraints of public service. Missing output format, failure modes, and whether audits are read-only vs. generating reports. Adequate but incomplete behavioral picture.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly constructed sentences with zero redundancy. First sentence establishes core operation; second sentence provides critical deployment context. Front-loaded with actionable verb and scope.

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 9-parameter security tool with no output schema, description establishes the core conceptual model (staging, audit surfaces) and current limitations. Absence of output description or detailed prerequisite chain prevents higher score despite good annotations in schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage (baseline 3). Description adds valuable conceptual framing, mapping 'secrets' and 'static' parameters to 'security-focused audit surfaces' and explaining the 'staged local files' concept that ties together 'files', 'paths', and 'config' parameters. Elevates beyond raw schema 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?

Clear verb+resource combination ('Run... security-focused audit surfaces against staged local files'). Specifies exact capabilities (secret scanning, local-config static analysis) and target (staged local files). Distinguishes from siblings like 'lint' or 'test' through explicit security focus and specific techniques mentioned.

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?

Provides implicit guidance through public service limitations ('currently means secret scanning...'), constraining expectations about available features. However, lacks explicit comparison to sibling tools like 'lint' or 'deps' (noted as disabled) to guide selection, or prerequisites for staging files.

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

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

No annotations provided, so description carries full disclosure burden. It mentions 'clean runtimes' (isolation) and 'short-lived' (duration constraints), but omits critical behavioral details like resource limits, file cleanup after execution, blocking behavior, or what output/return format to expect.

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?

Single sentence that is appropriately front-loaded with the core action ('Run... benchmark jobs'). The trailing negative clause ('without turning...') slightly reduces efficiency but does not significantly waste space.

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 6-parameter execution tool with no output schema and no annotations, the description covers primary purpose and isolation model but lacks completeness regarding return values (timing metrics), cleanup behavior, or prerequisite setup requirements.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (all 6 parameters documented), establishing a baseline of 3. The description adds minimal parameter-specific context beyond the schema, though 'small, short-lived' implicitly contextualizes the 'timeout' and 'iterations' parameters.

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 runs 'small, short-lived benchmark jobs' to 'compare simple timing behavior' using 'clean runtimes'—specific verb, resource, and scope. The 'without turning Squire into a full performance platform' clause helps distinguish its limited scope, though it doesn't explicitly contrast with siblings like 'test'.

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?

Provides implicit constraints ('small, short-lived', 'without turning... into a full performance platform') that suggest when to use it versus heavy profiling platforms, but lacks explicit 'when to use' guidance or comparison to related sibling tools like 'test'.

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

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

With no annotations provided, the description carries full burden. It successfully discloses key traits (headless, offline, sandboxed, optional artifact download) but fails to clarify the execution model, persistence, or what the tool returns (success codes, paths, console output?).

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?

Single, well-structured sentence front-loaded with the core action. Every clause earns its place: engine type (headless Chromium), environment (constrained offline sandbox), and side effects (artifact downloads). No redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a tool with 8 parameters and no output schema, covering the sandbox environment and artifact generation. However, given the lack of annotations and output schema, it should disclose return values or execution results to be 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 coverage is 100%, establishing baseline 3. The description adds semantic context by linking 'download screenshots' to the screenshot and download_artifacts_dir parameters, and 'offline' to the url parameter's file:// restriction, but does not elaborate beyond schema definitions.

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?

Description clearly states the specific action (Run headless Chromium), environment (constrained offline sandbox), and capabilities (download screenshots/artifacts). It distinguishes from siblings by specifying browser automation in a sandboxed, offline context.

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 'offline sandbox' constraint implies boundaries (file:// URLs only), but there is no explicit guidance on when to use this versus alternatives, prerequisites for the script parameter, or warnings about the timeout behavior.

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

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

No annotations are present, so the description must carry the full burden. It disclose the side effect of downloading artifacts locally and mentions 'clean environments,' but omits critical behavioral details: whether the operation is destructive to local files, environment lifecycle/cleanup, authentication requirements, or what the return value/response contains.

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?

Single, well-structured sentence (20 words) that is front-loaded with the core action. Every clause earns its place: 'offline packaging' defines mode, 'build sanity checks' defines purpose, 'clean environments' defines isolation, and 'optionally pull... locally' defines the download behavior. No redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 100% schema coverage, the description appropriately focuses on workflow intent rather than repeating parameter definitions. However, with no output schema provided, the description should ideally explain what success returns (e.g., build logs, artifact locations, status), which it omits. Adequate but has a clear gap in return value documentation.

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%, establishing a baseline of 3. The description adds conceptual context for 'download_artifacts_dir' by mentioning pulling artifacts back locally, and implies staging via the build context, but does not augment the schema's descriptions of 'targets,' 'timeout,' or the specific semantics of the staging parameters.

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?

Clearly states the action ('Run offline packaging and build sanity checks') and context ('clean environments'), plus the optional artifact retrieval. However, it does not explicitly distinguish from the 'compile' sibling tool, which may also perform build 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?

Provides implicit context through terms like 'offline' and 'clean environments' suggesting isolated builds, but lacks explicit guidance on when to use this versus 'compile' or other build-related siblings, and omits prerequisites or exclusion criteria.

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

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

No annotations provided, so description bears full disclosure burden. Adds useful context about 'clean toolchains' (isolated environments) and 'checks' (verification purpose), but omits critical behavioral details like whether outputs are preserved, if the operation modifies source directories, or specific toolchain side effects.

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?

Single dense sentence that front-loads the action ('Run...'). Every clause earns its place: 'target-specific' modifies the action, 'clean toolchains' describes the environment, and the negative constraint efficiently differentiates scope without wasted words.

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 4-parameter tool with complete schema documentation and simple types. However, given the lack of annotations and output schema, gaps remain in behavioral disclosure regarding output handling and side effects that would be necessary for an agent to fully trust the 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?

Input schema has 100% description coverage, establishing a baseline score of 3. The description mentions 'target-specific' and 'Go or Rust' which align with the 'targets' and 'language' parameters, but does not add substantial semantic detail, validation rules, or format syntax beyond what the schema already documents.

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?

Uses specific verb phrase 'Run...compilation checks' and identifies specific resources 'Go or Rust'. Explicitly distinguishes from the sibling 'build' tool via the scope constraint 'without turning Squire into a full CI or release system', clarifying this is for verification, not artifact generation.

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?

Provides clear scope boundaries by stating what the tool is NOT for (full CI/release system), which implicitly guards against inappropriate use for release builds. However, lacks explicit naming of the 'build' sibling as the alternative for those use cases.

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

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

With no annotations provided, the description carries the full burden. It successfully conveys 'disposable remote runtime' (indicating ephemeral state) and available libraries, but lacks critical behavioral details for a code-execution tool: isolation guarantees, side effects, network access, or how outputs are captured (beyond the schema parameters).

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 16-word sentence that front-loads the action ('Run Python...') and efficiently packs in the runtime characteristics ('disposable remote') and capabilities ('pandas, polars, and pyarrow'). Zero waste, 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?

For a 5-parameter code execution tool with no output schema and no annotations, one sentence is minimally sufficient. It covers the execution environment and available libraries, but lacks completeness regarding safety model, artifact lifecycle, or execution guarantees that would be expected for arbitrary code execution.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, establishing a baseline of 3. The description adds crucial semantic context for the 'script' parameter by specifying the available data-processing libraries (pandas/polars/pyarrow), which informs the agent what kind of Python code can successfully execute. However, it does not elaborate on input/output mechanics despite the schema being present.

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 provides a specific verb ('Run') plus resource ('Python data-processing jobs') and clearly distinguishes from siblings like 'sql', 'solve', and 'quantum_simulate' by specifying the pandas/polars/pyarrow data-processing environment. It establishes both the action and the specific domain.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit when-to-use or alternatives are listed, but the mention of pandas, polars, and pyarrow provides implied usage guidance—suggesting this tool is for DataFrame-based data manipulation rather than general computation or SQL queries. However, it lacks explicit guidance for choosing between this and siblings like 'sql' or 'solve'.

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

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

No annotations provided, so description carries full burden. Adds 'clean environment' execution context and crucial service availability status (rejects jobs) that is not in the schema. Does not describe output format or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero waste. First establishes purpose, second states critical operational limitation. No redundant information. Front-loaded with the core validation purpose.

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?

Appropriate for 4-parameter tool with full schema coverage. Mentions key service limitation and execution environment ('clean'). Missing output description but no output schema exists to require it. No annotations to supplement.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (file, language, targets, timeout all documented). Description adds context that the file is a 'dependency manifest' but does not elaborate on parameter interactions or syntax beyond what the schema provides. Baseline 3 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?

Clear specific verb 'Validate' with resource 'dependency manifests' and scope 'clean environment'. Identifies the domain (dependencies) which distinguishes from siblings like 'build' or 'test', though could explicitly differentiate from 'verify'.

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?

Provides critical limitation that 'public zero-egress service currently rejects deps jobs', which functions as a when-not-to-use warning. However, lacks explicit guidance on when to choose this over siblings like 'verify', 'build', or 'test' for validation tasks.

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

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

No annotations provided, so description carries full disclosure burden. It explains conceptual behavior well (discovery surface) but omits technical details like return format (text vs structured), caching behavior, or output length limits. Adequate for a low-risk help tool but lacks richness expected when annotations are absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero waste. First sentence defines functionality; second sentence establishes workflow position ('canonical discovery surface...'). Every word earns its place—efficiently front-loaded with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Appropriately complete given low complexity (1 optional string param) and lack of output schema. Sufficiently explains the tool's role in the ecosystem. Minor gap: does not describe output format (human-readable text? JSON?) which would help given no output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% description coverage ('Optional command path, such as verify or quantum simulate'). With high schema coverage, baseline is 3. The description adds minimal semantic detail beyond the schema, merely reinforcing the 'help for a specific command' use case.

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?

Explicitly states what the tool does: 'Show the top-level Squire command catalog or help for a specific command.' Uses specific verb 'Show' with clear resources (catalog/help). References sibling commands 'verify' and 'quantum simulate' in the description, distinguishing this discovery tool from the operational 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?

Strong contextual guidance: 'This is the canonical discovery surface for humans and agents before choosing a command.' Clearly positions when to use it (before choosing other commands). Lacks explicit 'when not to use' guidance or specific alternative comparisons, falling short of a perfect 5.

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

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

No annotations provided, so description carries full burden. Adds valuable context about 'fresh toolchain' isolation, but omits critical safety profile (read-only vs destructive/fixing), output format, or failure behavior. The word 'fixed' is ambiguous (pre-configured vs auto-fix).

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?

Single 19-word sentence with zero waste. Front-loaded with action verb, every clause earns its place explaining both what it does and why (environment drift prevention).

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 5 parameters with full schema coverage, description adequately explains execution context (isolation) but lacks output behavior disclosure and safety profile given no annotations or output schema exist.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, providing complete parameter documentation. Description does not add parameter-specific semantics (e.g., path formats, target globs) beyond what the schema already defines, earning 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?

Specific verb 'Run' with clear resources 'lint and static-analysis tools'. The phrase 'fresh toolchain' effectively distinguishes from siblings like build, compile, test, and verify by emphasizing isolated environment execution.

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?

Implies clear usage context: use when you need to avoid 'local environment drift' affecting results. While it doesn't explicitly name alternatives, the value proposition (fresh toolchain vs local) guides selection. Lacks explicit prerequisites or 'when not to use' 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?

With no annotations, description carries full burden and discloses key traits: 'disposable' implies temporary/isolated execution, 'ffmpeg installed' declares dependencies, and 'optionally download' clarifies persistence behavior. However, it omits critical execution details like timeout enforcement behavior, cleanup guarantees for undownloaded files, or security boundaries.

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?

Single sentence of ~20 words with zero waste. Information is front-loaded ('Run Python media jobs'), followed by environment constraints ('disposable remote runtime with ffmpeg'), and closes with side effects ('optionally download').

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 5-parameter remote execution tool without output schema or annotations, description adequately covers the job lifecycle (execution environment, optional artifact retrieval). Minor gaps remain regarding return value structure and failure modes, but sufficient for tool selection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, establishing baseline 3. Description adds semantic value by mapping 'Python media jobs' to the required 'script' parameter and clarifying that 'download_artifacts_dir' corresponds to generated artifacts from the job, connecting the high-level operation to specific schema elements.

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?

Description provides specific verb ('Run') with clear resource type ('Python media jobs'), environment context ('disposable remote runtime with ffmpeg'), and implicitly distinguishes from siblings like 'compile', 'build', or 'data' via the 'ffmpeg' and 'media' specificity.

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?

Provides implied usage context through 'ffmpeg installed' (suggests media processing workloads) and 'optionally download' (indicates persistence choice), but lacks explicit guidance on when to prefer this over 'data' or 'compile' siblings, 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?

With no annotations provided, the description carries the full disclosure burden. It successfully conveys environmental isolation ('offline...image'), temporary staging, and artifact generation. However, it omits critical behavioral details: what the tool returns upon completion (execution logs? results JSON?), cleanup behavior of the staged files, and any side effects on the local system beyond the optional download.

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?

Dense but efficient single sentence with zero waste. Progresses logically from staging to execution to artifact handling, front-loading the core action. Each clause maps directly to a parameter or critical environmental constraint.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema and annotations, the description should explain the return value (simulation results, exit codes, logs), but it only mentions side-effect artifacts. While parameters are well-covered by the schema, the execution lifecycle (cleanup, timeouts, error states) remains undocumented.

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 100% schema coverage, the baseline is 3. The description adds valuable domain context beyond the schema: 'small' reinforces size constraints, 'Python/Qiskit' clarifies the expected file types for the 'files' parameter, and 'Qiskit Aer image' explains why 'backend' is limited to aer_simulator. This framing helps agents correctly map intent to parameters.

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 provides specific verbs (stage, run, download) and identifies the unique resource (Python/Qiskit files, Qiskit Aer image). It distinguishes this from generic build/compile siblings by specifying the quantum stack. However, it stops short of explicitly positioning against hypothetical general-purpose execution tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description contains implicit constraints ('small' file set) but provides no explicit guidance on when to use this tool versus alternatives, prerequisites (e.g., Qiskit knowledge), or when to avoid it (e.g., for production-scale quantum jobs).

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?

Discloses execution environment ('fresh disposable sandbox') and scope ('bounded'), but lacks critical behavioral details required in absence of annotations: output format, sandbox lifecycle, side effects, or failure modes. No indication of what constitutes job success/failure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence of 10 words with high information density. Every element serves a purpose: verb, scope, technology constraints, and execution environment. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (execution tool, 4 params, no annotations/output schema), the description covers the essentials but leaves gaps. Adequate for invocation, but missing behavioral details regarding return values, persistence, or sandbox teardown that would make it 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?

With 100% schema coverage, baseline is 3. The description adds valuable domain context: 'Z3 or MiniZinc' clarifies valid 'solver' values, 'bounded' contextualizes the timeout parameter, and 'jobs' frames the file/data parameters' purpose.

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?

Specifies exact action ('Run'), resource type ('solver jobs'), and valid inputs ('Z3 or MiniZinc'). The 'fresh disposable sandbox' adds execution context. However, it does not explicitly differentiate from potentially related siblings like 'verify' or 'quantum_simulate'.

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?

Implies usage context through 'bounded' (suggesting time/resource constraints) and specific solver technologies. However, lacks explicit when-to-use/when-not-to-use guidance or comparison to alternatives like 'compile' or 'verify'.

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

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

With no annotations provided, the description carries the full burden. It successfully conveys the sandbox nature ('fresh disposable database'), implying isolation and safety for destructive operations. However, it omits details about return values, error handling behavior, and whether the sandbox persists across calls.

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?

Single dense sentence with zero waste. Front-loaded with the action verb 'Run', covers dialects (SQLite/Postgres), operations (schema/query/migration), and environment (sandbox) 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?

Given 7 parameters and no output schema, the description is minimally adequate. The 'sandbox' disclosure is essential for a SQL execution tool, but gaps remain regarding output format, error behavior, and clarification of the migration 'validation' process versus actual application.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, establishing a baseline of 3. The description mentions 'SQLite or Postgres' and 'schema, query' which map to parameter names, but doesn't add semantic details like parameter relationships (e.g., that query executes after schema) or valid file formats beyond the schema definitions.

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 specific verbs ('Run') and resources ('schema, query, and migration validation') with clear scope ('SQLite or Postgres'). It distinguishes from siblings like 'browser', 'media', or 'audit' by specifying database-specific operations and the sandbox environment.

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?

Implies usage through keywords like 'validation' and 'sandbox' (suggesting testing/isolation use cases), but lacks explicit when-to-use guidance or comparisons to siblings like 'data' or 'verify' that might overlap in functionality.

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

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

With no annotations provided, the description carries the full disclosure burden. It valuably mentions 'clean runtimes' (isolation) and 'target matrix' (execution model), but fails to disclose critical execution traits like side effects/destructiveness, blocking behavior, or what constitutes success/failure return values.

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?

Single 16-word sentence with zero waste. Every phrase earns its place: 'small or medium' defines scope, 'clean runtimes' defines environment, 'target matrix' defines execution pattern, and the language list defines supported platforms. Front-loaded with the primary action.

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 5-parameter tool with complete schema coverage, but the lack of output schema means the description should ideally hint at return behavior (test results, pass/fail signaling). The description successfully covers input intent and execution environment but omits output/completion semantics.

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?

Despite 100% schema coverage (baseline 3), the description adds significant semantic context: 'target matrix' explains the execution model for the 'targets' parameter, 'clean runtimes' describes the execution environment, and 'Python, Node, or Bash' reinforces valid language inputs. This contextual layer meaningfully augments the schema definitions.

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 'Run' and resource 'test jobs' with specific scope modifiers ('small or medium', 'clean runtimes') and supported languages ('Python, Node, or Bash'). It implicitly distinguishes from siblings like 'build' or 'compile', though it doesn't explicitly differentiate from similar testing tools like 'verify' or 'bench'.

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 scope guidance ('small or medium test jobs') implying suitability boundaries, but lacks explicit when-not-to-use guidance or named alternatives. With siblings like 'verify', 'bench', and 'audit' present, the absence of explicit differentiation guidance is a notable 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?

With no annotations provided, the description carries the full burden. It discloses the 'fresh Linux containers' execution environment implying isolation, but lacks details on container lifecycle (cleanup/persistence), side effects, output format, or resource constraints. 'Fresh' adds some behavioral context but coverage is incomplete for a code execution 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?

Single, efficient sentence with zero waste. Front-loaded with verb 'Run'. Every word ('small', 'fresh', 'across') adds specific meaning about scope and environment. Length is appropriate for the parameter complexity.

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 5 parameters with 100% schema coverage but no annotations and no output schema, the description adequately covers the execution model but leaves gaps regarding return values, success/failure indicators, and interaction patterns between 'code' and 'file' parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, establishing baseline 3. The description maps 'inline snippets' to 'code', 'staged scripts' to 'file', and 'target images' to 'targets', providing conceptual framing, but does not add syntax details, constraints, or mutual exclusivity rules beyond what the schema already documents.

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?

Description provides specific verb ('Run'), resource ('small inline snippets or staged scripts'), and execution context ('fresh Linux containers across supported target images'). It clearly distinguishes from siblings like 'test', 'build', or 'compile' by emphasizing lightweight, containerized verification.

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 'small inline snippets' implies lightweight, quick verification use cases, but there is no explicit guidance on when to choose 'verify' over similar siblings like 'test', 'bench', or 'run'. No alternatives or exclusions are named.

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

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

With no annotations provided, description carries full burden. Lists return payload categories but omits operational traits: no mention of side effects (logging), authentication requirements, rate limits, or cache 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?

Single sentence, densely packed with specific return value categories. No redundancy, immediately front-loaded with actionable information.

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?

Absent output schema and annotations, the description compensates by enumerating return value domains (identity metadata, quotas, flags). Sufficient for a parameter-less identity tool, though structured return schema details would strengthen 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?

Zero parameters present per schema. Baseline score 4 applies as there are no parameters requiring semantic 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?

Specific verb 'Return' plus exact resource inventory (identity, trust tier, feature flags, token metadata, quotas). Clearly distinguishes from operational siblings like build/sql/compile by focusing on introspection/identity.

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?

Describes what data categories are returned, implying use for authentication/authorization checks, but lacks explicit when-to-use guidance versus sibling 'audit' or session initialization patterns.

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