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

With no annotations, the description carries the full burden, but it does disclose the significant behavioral fact: this writes files into four specific locations in the repository. It omits overwrite semantics, whether directories are created, and error behavior on a missing source file – gaps that matter for a tool that mutates the workspace.

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?

One dense sentence with the input front-loaded before the outputs – no filler. It is terse to the point of being cryptic for a reader who does not already know what a "scar" is, but nothing is wasted.

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

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

For a side-effecting build tool with two undocumented parameters, zero annotations, and no output schema, the description is thin. It never says what the call returns (a success flag, a list of written paths) or how partial `targets` selections behave.

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 0%, so the description must compensate and largely does not. The four listed outputs loosely map to the default `targets` values, but nothing states that `targets` selects which artifacts to emit, and `workspace_root` is completely unexplained.

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?

A specific verb ("Compile") plus an explicit source artifact (`.kintsugi/scars.json`) and four named destinations makes the operation unmistakable. It doesn't explicitly contrast with `kintsugi_scan_code` or `kintsugi_record_failure`, but the build/codegen nature is naturally distinct from 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?

There is no when-to-use guidance at all – nothing says this runs after scars are recorded, or that it is the final materialization step in the workflow. No prerequisites, no exclusions, and no mention of what to do if `.kintsugi/scars.json` does not exist.

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 supplied, so the description carries the full burden. The imperative "List" plus the qualifier "verified" implicitly establish a non-mutating read that returns only validated entries, but there is no disclosure of ordering, result limits, pagination, or how much data comes back. It adds some behavioral context but stops short of what an unannotated tool needs.

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

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

A single front-loaded sentence that names the resource first and the filters second, with no filler or repetition. The dense parenthetical earns its space by decoding the jargon a new agent would otherwise stumble on.

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 three-parameter read-only list tool with no output schema, the definition covers the what and the filter set but omits the return shape, ordering, and result-size behavior. Since there is no output schema to describe what a "Golden Scar" record contains, the description should have sketched that at least briefly.

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 0%, so the description must compensate, and it does identify all three parameters as filters and clarifies that min_severity is a threshold rather than an exact match. However, it says nothing about tag or language value formats, case sensitivity, or whether filters combine with AND/OR 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?

"List verified Golden Scars" gives a specific verb plus resource, and the parenthetical decodes the domain term as anti-pattern/fix pairs, so the agent can tell what the resource is. What's missing is any explicit differentiation from siblings such as kintsugi_scan_code, since nothing says whether this returns prior findings or new ones.

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 only enumerates filters, which implies a retrieval use case but never states when to reach for this tool versus kintsugi_scan_code or kintsugi_record_failure. There are no exclusions, no preconditions, and no workflow placement, leaving the agent to infer selection from the filter list alone.

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

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

With no annotations supplied, the description carries the full burden. It does disclose that state is written to `.kintsugi/scars.json`, which is useful, but says nothing about whether writes append or overwrite, whether duplicates are deduplicated, what 'self-verified' mechanically means, failure modes, or permissions.

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 the verb and artifact up front and no filler. It is efficient, but its brevity comes partly from leaning on unexplained domain vocabulary rather than from tight editing.

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 mutation-style tool with no annotations, no output schema, and five undocumented parameters, the definition is under-specified. An agent knows roughly what happens but not the required input combinations, the verification step, or the result; the persistence clause is the only behavioral detail present.

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

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

Five parameters exist with 0% schema description coverage, and the description explains none of them. It weakly implies that raw_trace and error_summary feed the compiled record, but gives no meaning for fixed_snippet vs offending_snippet, no indication that only the two required params are truly needed, and no note on the language default.

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 action chain (compile a failure into a record and persist it), and the destination file `.kintsugi/scars.json` anchors it. But 'Golden Scar' is undefined jargon, so an agent cannot be sure whether the artifact is a test case, a patch record, or a knowledge entry; it also never distinguishes itself from siblings like kintsugi_list_scars or kintsugi_scan_code.

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 call this rather than kintsugi_scan_code, kintsugi_list_scars, or kintsugi_compile_skills, and no stated preconditions (e.g., must a failure already have been scanned or listed?). The agent must infer the trigger condition from the name alone.

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

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

With no annotations, the description carries the full burden. It usefully signals determinism (no LLM inference) and the AST+Regex mechanism, but never states that the operation is read-only/non-mutating, nor what the result looks like or what happens when a scar matches. Key behavioral context is missing for an un-annotated 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?

A single front-loaded sentence with no filler, and the timing constraint is placed at the end where it reads naturally. 'Kintsugi Golden Scars' is domain jargon left unexplained, which slightly reduces immediate comprehensibility.

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

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

With no output schema and no annotations, the description should say what a scan yields (findings list? boolean verdict?) and how matches are reported. It covers what to scan and roughly when, but leaves the caller unable to predict the response shape.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds only marginal meaning by framing 'code' and 'file_path' as alternative input modes ('snippet or file path'); it says nothing about precedence when both are supplied or how 'language' interacts with file_path detection.

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 pairs a specific verb ('scan') with concrete inputs ('source snippet or file path') and a named rule set ('Kintsugi Golden Scars (AST + Regex)'). It is clearly distinguishable from the siblings (list_scars, record_failure, compile_skills), though it never explicitly contrasts itself with them.

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

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

There is an implicit usage trigger — 'before writing or committing' tells the agent this is a pre-write gate. But there is no guidance on what to do with a match, no when-not-to-use condition, and no routing to siblings such as record_failure after a finding.

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