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

The description adds meaningful context beyond the annotations: it discloses that the cache is optional and that its absence does not affect correctness. However, it does not explain side effects or consequences of the clear or prewarm operations. The annotations already signal this is not a read-only tool, and the description does not directly contradict 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?

The description is two sentences with no filler. It front-loads the critical caveat ('optional performance layer, NOT availability gate') and then gives a concrete usage directive. Every clause 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?

There is no output schema, so the description should clarify what each mode returns or changes, but it only explains the status mode. The behavior of clear, explain, and prewarm is left to inference, and the compact parameter is entirely unexplained. For a tool with four modes and no output schema, this is not complete enough.

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 documents mode with an enum and the minimal phrase 'Cache operation', while compact has no schema description at all. The description adds semantic value for mode=status but says nothing about the compact parameter or the meaning of clear/explain/prewarm. With schema coverage at 50%, this is only a partial compensation.

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 identifies the tool as cache management and enumerates the exact operations (status, clear, explain, prewarm). The phrase 'optional performance layer, NOT availability gate' sharply distinguishes it from the analysis-oriented sibling tools. An agent can immediately understand the resource and scope.

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

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

The description explicitly frames the cache as optional and explains that a disabled persistent cache does not block fresh static analysis, so an agent knows not to treat it as an availability dependency. It also gives a concrete directive: use mode=status to check memory and persistent cache state. It does not detail when to use clear/explain/prewarm, but the main context is clear.

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 establish that this is read-only, idempotent, non-destructive, and not open-world. The description adds useful scoping context ('pre/post edit review', 'single project root') but does not disclose behavior such as job lifecycle, pagination/output format, or what happens with mode-specific edge cases. This is adequate given the annotations, 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 two tight sentences with no filler. The front-loaded first sentence establishes core purpose and scope, and the second sentence delivers actionable routing guidance. Every clause 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?

The tool is complex: 10 parameters, 20 modes, and no output schema. The description covers workflow and mode selection well, but it does not explain return values or the behavior of job modes, leaving the agent to rely on schema descriptions alone. For a tool this flexible, a bit more guidance on outputs and job-mode expectations would be needed for full 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 coverage is 70%, and the description meaningfully enriches several parameters: it explains which mode to prefer for different scenarios and reinforces that the tool operates on a single root, not a workspace. It does not add detail for compact, direction, or language, but those are either defaulted or enum-covered, so the added guidance is net-positive.

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 identifies a specific verb and resource: 'Concrete pre/post edit review for a SINGLE project root when the target is known.' It also distinguishes itself from a sibling by stating that if the target is unclear, codelattice_workflow should be used first, so the agent understands this tool's niche without opening the schema.

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

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

The description gives explicit mode-selection guidance: use impact before editing, native_review after local diffs, breaking_change for public API concerns, and job modes for large repos. It also names the alternative tool and the condition that triggers it, making when-to-use 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 disclose read-only and idempotent behavior, so the description need not repeat that. It adds mode-specific behavioral context — e.g., 'job modes for large repos' implies non-blocking behavior, and 'static risk orientation' clarifies the tool does not execute code. Minor gap: no mention of output shape or pagination, but that is partially covered by the detail parameter in the schema.

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

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

Four sentences that front-load the core purpose and scope, then pack mode selection and sibling routing into two short follow-ups. No filler or repetition of schema contents. Every sentence 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 13-parameter tool with no output schema, the description provides essential orientation: it explains the central mode parameter, gives a decision tree for repo types, and points to sibling tools for the wrong context. Parameter-specific details (page, jobId, symptom, errorText) are left to the schema, which covers them adequately. It's complete enough for an agent to pick the right mode and root, though it doesn't describe response formats.

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 high (85%), so the baseline is 3. The description adds real meaning to the mode parameter by mapping each enum value to its intended use ('quick first, standard for module/risk review, deep for detailed static evidence, diagnose for issue localization, job modes for large repos'). This goes beyond the schema's terse enum names and compensates for the few uncovered 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?

Opening phrase 'Project-level analysis for a SINGLE project root' immediately names the resource and scope. It lists concrete outputs (structure, entry points, components, static risk orientation) and explicitly differentiates from codelattice_workspace for monorepo roots. This lets an agent distinguish it from siblings without opening 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?

Provides explicit mode-to-use-case mapping: quick first, standard for module/risk review, deep for static evidence, diagnose for issue localization, job for large repos. It also states when NOT to use this tool ('For monorepo/workspace roots, use codelattice_workspace or workflow explore first') and how to proceed after. This is exactly the when/when-not guidance the dimension asks for.

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 the tool read-only, idempotent, and non-destructive. The description adds meaningful behavioral context by stating the single-project-root prerequisite and describing the job lifecycle with progress tracking. It does not go into deeper edge cases, but the annotation coverage lowers the burden.

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 two focused, front-loaded sentences. The first sentence states the scope and resource, and the second gives actionable mode-selection guidance with no filler or repetition of schema details.

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 complex 14-parameter, multi-mode tool, the description covers the main decision paths and the job workflow while the schema covers the remaining parameter details. It does not explicitly mention graph mode or output shape, but the annotated read-only safety profile and rich schema make the definition 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?

Schema description coverage is 86%, so the individual parameter descriptions already carry most of the meaning. The tool description adds only modest value by clarifying the root scoping and the job-mode sequencing, so the baseline score 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 identifies the tool as performing 'symbol-level queries' scoped to 'a SINGLE project root,' and it differentiates internal query modes (search/context vs. callers/callees/call_chains). This distinguishes it from siblings like codelattice_workflow or codelattice_cache, which are not symbol-query tools.

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

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

The description gives explicit mode-selection guidance: use search/context when a symbol or name is known, use callers/callees/call_chains for relationships and flow, and use mode=job followed by job_status/job_detail for large projects. This directly tells an agent when to choose which 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?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety burden is low. The description adds the routing/orchestration role and first-use behavior beyond the annotations, but it does not disclose what the tool returns, how execution via the execute parameter behaves, or how modes resolve. There is no contradiction with annotations.

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

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

The description is three short sentences with no filler. It front-loads the tool's identity and purpose, then gives actionable routing guidance. Every sentence 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 17-mode router with no output schema, the description covers only a subset of modes and says nothing about execution behavior or response shape. The rich schema and annotations compensate significantly, so it is not inadequate, but there are clear gaps for the remaining workflow modes.

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 about 88%, and the mode parameter already explains several workflow scenarios. The description itself adds no parameter-level detail, so it earns the baseline 3 for relying on a well-covered schema rather than compensating with additional 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 identifies a specific role and resource: 'AI intent router and orchestration layer.' It also distinguishes itself from other CodeLattice tools by positioning itself as the first-stop entry point when the agent is unsure which tool to call, so there is no ambiguity about what this tool is for.

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

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

It gives explicit usage context: 'Use this FIRST when unsure which CodeLattice tool or root to call' and routes specific intents to ask, explore, diagnose_issue, and before_edit. It even gives a when-not condition for before_edit, though it does not name sibling tools as explicit alternatives or cover all 17 modes.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds only the notion of engine-backed job mode and does not disclose behavior such as job lifecycle, response shape, or how modes like job_cancel relate to the read-only 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?

Two sentences, front-loaded with the tool's purpose and followed by the single most important usage caveat. No filler or repetition of schema details.

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 plus schema cover the main modes, but there is no output schema and no explanation of what the 'full' mode returns or how target/impact mode works. For a 9-parameter multi-mode tool, the description is useful 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?

Schema coverage is 67% and the description adds high-level mode guidance, but it does not explain parameters like root, target, compact, maxDepth, or direction beyond what the schema already says. It is adequate but does not compensate for the remaining undocumented 33% of 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 identifies a specific resource (workspace/monorepo roots) and a concrete task (analysis for boundaries, dependency graph, cross-project impact, overview, or engine-backed job mode). It distinguishes itself from codelattice_project by instructing to use that tool only after selecting a manifest-backed project root.

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?

'Use this on workspace roots; use codelattice_project only after selecting a manifest-backed project root' is an explicit routing rule with a condition and an alternative. It also signals large-workspace handling through the engine-backed job mode.

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