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

With no annotations, the description carries the full burden of disclosing behavior. 'Analyze' hints at a read-only style operation, but the description does not clarify whether this reads static files, invokes providers, or has side effects, nor does it mention prerequisites or operational impact.

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 single sentence is short, but it is under-specified rather than appropriately concise. It front-loads 'Analyze' but then trails off into unclear coupling jargon, which does not earn its place as meaningful guidance.

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 definition is inadequate for a tool with three parameters, zero annotation coverage, and 26 sibling tools that could easily be confused with it. Even with an output schema present, the description leaves the core subject, required application_path semantics, and relationship to sibling tools completely unexplained.

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% and the description mentions none of the three parameters: application_path, target, or target_platform. The description adds no meaning beyond the schema's bare field names, and it fails to compensate for the lack of 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 uses a specific verb ('Analyze') and names a resource ('provider invocation and adjacent tool/output couplings'), giving some sense of focus. However, the phrasing is vague and jargon-heavy, and it does not clearly differentiate this tool from siblings like analyze_prompt or analyze_regressions.

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 about when to use this tool versus the many sibling tools such as compare_outputs, prepare_invocation_migration, or analyze_prompt. No context, exclusions, or alternative-selection criteria are provided.

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 behavioral burden. It successfully communicates a conservative, non-inferential analysis stance and implies a read-only action, but it does not explain what 'conservative' concretely means, whether any side effects exist, or what characteristics are examined. The output schema can cover return shape, but broader behavioral context is thin.

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 words, so it is easy to scan. 'Conservatively' and 'without inference' are close to redundant, but the overall structure is appropriately sized for a one-parameter tool.

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

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

For a tool with 26 siblings and no annotations, the definition is too thin: it gives no clue which prompt characteristics are analyzed, no contrast with validate_prompt or analyze_invocation, and no statement about when it is the right choice. The output schema reduces return-value ambiguity, but selection context is still a meaningful gap.

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 no description for the only parameter, giving 0% coverage, and the tool description does not compensate. It does not explain the expected form of 'prompt', any constraints, or examples, so the agent gets no semantic value beyond the property name itself.

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 ('analyze') and resource ('prompt'), and adds the qualifiers 'conservatively' and 'without inference' to convey a descriptive, non-speculative intent. It is clearer than a tautology, but it does not define which 'characteristics' are covered or explicitly distinguish the tool from siblings like validate_prompt and analyze_invocation.

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 about when to use this tool versus the many siblings; the description never names alternatives or conditions. 'Conservatively' and 'without inference' describe how the analysis should behave, not the situations that should trigger the tool, leaving selection largely to 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?

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only says a report is returned. It does not disclose whether the tool mutates anything, what criteria define regressions, how categories are determined, or any operational constraints.

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 with no filler and front-loads the key action and deliverable. It is efficiently structured, though its brevity comes at the cost of useful 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?

The input schema is highly underspecified, and the description does not compensate by explaining how to construct or obtain the 'run' object or what the categorized report will contain. Even with an output schema present, the tool is not adequately documented 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?

Schema description coverage is 0%, and the sole parameter 'run' is an opaque object with additionalProperties true. The description adds the minimal meaning that 'run' refers to an evaluation run, but it does not explain what properties the run object should contain or how the tool uses them.

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 clear verb ('Return') and a specific resource ('a structured categorized regression report for an evaluation run'), making the core function understandable. However, it does not distinguish itself from sibling tools like generate_migration_report or run_migration_eval, so it stops short of full differentiation.

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 about when to use this tool versus alternatives. The phrase 'for an evaluation run' hints at context, but the description never states conditions, prerequisites, or exclusions, leaving the agent to infer usage 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 must fully convey behavioral traits. It does disclose that the combination is 'deterministic' and explicitly warns that 'agent agreement is not evidence,' which is useful. However, it says nothing about side effects, permission requirements, reversibility, or any state changes. For a tool that processes multiple objects, this is minimal behavioral disclosure.

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 that places the core action first and the caveat second. It is very concise and front-loaded, with no filler. The brevity is commendable, though it sacrifices critical detail that would improve other dimensions.

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?

Although an output schema exists (so return values need not be described), the tool still lacks essential context for correct invocation. The description does not clarify what the 'request' object should contain, how research and review relate, or what constitutes a valid consensus. For a tool with three untyped objects, this is incomplete and could lead to mis-calls.

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% and the description provides no explanation of the three parameters (research, review, request). It mentions 'research and review' only in passing and omits 'request' entirely. No field meanings, expected structure, or relationships are given, leaving the agent with no guidance on what to populate.

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 ('deterministically combine') on specific resources ('research and review'), making the core purpose clear. It also adds a distinctive caveat ('agent agreement is not evidence') that hints at its role in the workflow. However, it does not explicitly state what the tool produces (e.g., a consensus document or analysis), relying on the output schema for that detail, which slightly limits clarity.

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 like validate_research_result or generate_migration_report. The description gives no context on the expected input format, prerequisites, or the decision flow that leads to invoking this tool. This is a significant gap for an agent navigating a large sibling set.

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 burden, and it does well by disclosing immutability, expiration, and fail-closed behavior without hidden work. It does not detail every side effect, but it adds meaningful behavioral context beyond 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?

Two concise sentences front-load the core purpose and then add the key fail-closed constraint. Every sentence earns its place with no fluff.

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?

Although an output schema exists and fail-closed behavior is stated, the definition omits parameter meanings, usage alternatives, and side effects beyond immutability/expiration. With no annotations and 0% schema description coverage, an agent still has significant gaps to bridge before invoking it confidently.

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; 'run workspace' and 'expiring' map weakly to run_dir and ttl_days, but no parameter is actually explained. shadow_canonical, now, and ttl_days semantics remain entirely opaque.

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 ('Finalize') and resource ('run workspace' into an 'immutable, expiring session overlay'), which is far more informative than a tautology and separates this from generic build tools. It does not explicitly compare against siblings, but the overlay/fail-closed language makes the tool's role 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?

It states a clear precondition: research/review artifacts must already exist, and stages still needing an agent cause failure. This implies the tool should be run only after earlier research stages complete, but it never names alternatives or says when not to use it.

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 of behavioral disclosure. It does add useful context: it operates on reviewed facts, uses a fixed date, and avoids live research. However, it does not disclose side effects, caching behavior, error conditions, or whether the operation is strictly read-only, which remains important for a tool with zero annotation coverage.

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. It front-loads what the tool does and its key constraint, though it is perhaps too concise to also cover parameter semantics.

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

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

The output schema reduces the need to describe return values, but the description still lacks essential context: what an 'identifier' refers to, how as_of_date behaves, and how this tool relates to the many similar siblings. For a tool with no annotations and zero schema coverage on parameters, this is a significant completeness gap.

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, but it does not explicitly explain 'identifier' or 'as_of_date'. The phrase 'at a fixed date' loosely maps to as_of_date, but 'identifier' is completely unexplained, leaving the agent without meaningful guidance for the one required parameter.

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 ('interpret') and resource ('reviewed lifecycle facts') and adds a temporal scope ('at a fixed date') and a behavioral boundary ('without live research'). It is clear enough to distinguish this from live-data tools, though it does not explicitly name a sibling it differs from.

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 'without live research' implies this tool should be used when the agent needs a static, reviewed snapshot rather than current live information. This gives some usage context, but there is no explicit statement of when to prefer this tool over alternatives or when it should not be used.

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 responsibility for behavioral disclosure. It does reveal a key behavior: the tool returns an explicit state among same/different/unsupported/unknown, which clarifies the output contract. However, it does not mention whether the operation is read-only, whether it can make live pricing calls, or how unsupported/unknown states arise, leaving meaningful behavioral gaps.

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 scoped sentence with no redundancy. It front-loads the primary behavior and enumerates the possible comparison states efficiently. Nothing in the sentence 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?

Given seven parameters and no annotation support, the description is far too thin to be considered complete. It addresses only the return value shape and leaves input semantics, usage context, and behavioral details unexplained. The presence of an output schema reduces the need to document return values, but not the need to explain how to invoke the comparison 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 0%, so the description must compensate by explaining inputs, but it does not. The 'source' and 'target' strings are not described, and the optional endpoint, platform, and include_live_pricing parameters are entirely unexplained. An agent cannot reliably know what values or formats are 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?

The description 'Return explicit same/different/unsupported/unknown comparison states' makes clear the output is a comparison verdict, but it never states what is being compared. The tool name 'compare_models' and the 'source'/'target' parameters imply two models, but the description itself is vague about the resource and the operation's scope. It is not a tautology, but it lacks the specificity needed to fully understand the tool's 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?

There is no guidance about when to use compare_models versus any sibling tool. The description only says what it returns, not when it is appropriate or preferable to alternatives like compare_outputs or resolve_model. No exclusions or conditions are stated.

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 carries the full burden of behavioral disclosure. It does state that comparison is 'deterministically,' which is a meaningful behavioral trait, but it does not disclose side effects, mutation, authorization requirements, error behavior, or what happens when inputs are incomplete or mismatched.

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 focused sentence with no filler. It front-loads the action and includes the key behavioral qualifier without wasting 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?

An output schema exists, so return-value details are covered, but the description still lacks essential context about what constitutes a valid 'evaluation result,' what fields are expected inside the arbitrary nested objects, and how the deterministic comparison is performed. For a tool with two freeform object parameters and no annotations, this is a minimal definition with notable gaps.

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 for undocumented parameters. It labels source_result and target_result as 'paired source/target evaluation result,' providing some context, but it does not explain the expected structure, required nested fields, or how the pairing is defined. Given both parameters are free-form objects, this is insufficient.

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 and resource: 'compare one paired source/target evaluation result deterministically.' It clearly indicates what the tool does and adds a useful qualifier ('deterministically') that distinguishes the behavior. It doesn't explicitly name sibling tools, but the focus on source/target evaluation results is enough to distinguish it from compare_models.

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 alternative tool guidance is provided. The description only implies its use for paired source/target evaluation results, with no mention of when it should not be used or which siblings like validate_research_result or compare_models might be more appropriate.

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 must disclose behavior itself, but it only mentions that the scan is 'local' and 'user-scoped.' It does not explain what creating a research request entails, side effects, prerequisites, or how the request is processed. The term 'bound' is unclear and could be a typo, further reducing transparency.

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 short, but brevity comes at the cost of meaning. It is a single, cryptic sentence with no structure or front-loaded clarity, and it reads more like an under-specified tagline than an informative definition.

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?

This is a complex tool with six parameters, five required fields, nested objects, and an output schema, yet the description provides almost no operational context. It does not explain how to construct the request, what the output represents, or how this relates to the migration workflow. The description is fundamentally inadequate for reliable tool selection and 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 0%, so the description must compensate by explaining parameters, but it mentions none of the six parameters. Terms like 'user-scoped' and 'missing/stale facts' do not map clearly to required fields such as application, run_id, source, target, or as_of. The agent is left entirely to the schema, which lacks 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 uses verbs like 'scan' and 'bound' but never states that the tool creates a migration research request, which is the core action implied by the name. 'Bound explicit user-scoped research to missing/stale facts' is vague and does not clearly identify the resource being acted upon. It does not distinguish the tool from siblings like scan_application or validate_research_result.

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 'missing/stale facts' hints at a trigger condition, but there is no explicit guidance on when to use this tool versus alternatives. No alternatives are named, and there are no exclusion criteria or usage context provided.

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 behavioral transparency burden. It usefully discloses that the estimate is derived from checked-in canonical pricing, implying a deterministic, non-live computation rather than a network-dependent query. It does not mention side effects, but the verb 'estimate' strongly indicates a read-only calculator.

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. Every word contributes to defining the action, object, and pricing source, making it highly efficient.

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 output schema exists, so return values are covered, and the core purpose is clear. However, with five required parameters and zero parameter descriptions, the description is incomplete for confident invocation, especially regarding what source/target refer to and what time period 'recurring' implies.

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%, and the description does not compensate by explaining source, target, requests, or token units. While parameter names are somewhat self-explanatory, 'source' and 'target' are ambiguous without migration context, and the description adds little to the raw 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 uses a specific verb ('Estimate') and a clear resource ('recurring token cost') with a defined data source ('checked-in canonical pricing'). It distinguishes itself from sibling query_live_pricing by explicitly anchoring to canonical, not live, pricing.

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: use this when estimating recurring token costs based on checked-in canonical pricing rather than live rates. It does not explicitly name alternatives or state when not to use it, but the canonical-pricing qualifier is a strong usage signal.

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 must carry the full burden of behavioral disclosure. It states that the tool binds a corpus to a manifest, implying a creation/persistence action, but does not specify whether this is a read-only operation, whether it overwrites existing suites, or what side effects occur. The term 'deterministic' hints at properties of the output but not at tool behavior. This is a significant gap for a tool that likely has 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?

The description is a single, concise sentence that front-loads the core action without unnecessary fluff. It is well-structured for quick parsing, though it could have been slightly more explicit about the parameters in the same length.

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 has 3 parameters, nested objects, and an output schema, this description is far too brief. It does not explain what a valid 'case' looks like, what 'deterministic' means in practice, how the migration_plan should be structured, or what the output (bind) represents. The presence of an output schema does not reduce the need to explain inputs and behavior. An agent would likely need to inspect the schema and make many assumptions to use this 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 0% (no property descriptions), so the description must compensate. It mentions 'migration manifest' (likely migration_plan) and 'evaluation corpus' (likely cases), but does not map these terms directly to the schema parameters or explain their structure. It also omits the 'name' parameter entirely. The agent cannot infer parameter formats, relationships, or requirements from this description.

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 ('Bind') and names both the input (migration manifest) and the product (deterministic evaluation corpus). It distinguishes itself from siblings like run_migration_eval (which would execute the suite) and generate_migration_plan (which creates the plan) by indicating it creates a binding between the two. However, 'Bind' is less idiomatic than 'generate' or 'create', and the phrase 'evaluation corpus' is slightly vague without further 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 description gives no indication of when to use this tool versus alternatives. It does not mention, for example, that this tool is a precursor to run_migration_eval, or that it should be used after generate_migration_plan. An agent would have to infer usage from the tool name and siblings, which is insufficient.

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 behavioral burden. It usefully discloses that no files are written, implying the manifest is returned rather than persisted. However, it does not clarify whether the tool reads from application_path, whether there are other side effects, or what the generated manifest contains beyond being 'actionable'.

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 efficiently conveys the core purpose and the notable non-file-writing behavior.

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 tool with no annotations, the one-sentence description is too thin. It leaves parameter semantics and sibling differentiation unresolved; the output schema exists, but the agent still cannot reliably determine when or how to call this 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?

Schema description coverage is 0%, so the description must compensate, but it does not explain source, target, source_platform, target_platform, or application_path. The parameter names hint at a migration direction, but an agent cannot determine the expected value formats or relationships between source/target and source_platform/target_platform.

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 ('Generate'), a concrete deliverable ('actionable application-level migration manifest'), and a clear non-effect ('without writing files'). This distinguishes it from sibling report/session-plan tools even without naming 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?

The description gives no explicit guidance on when to choose this tool over generate_migration_report, generate_session_migration_plan, or other migration-related siblings. The 'without writing files' phrase implies a read-only intent but does not state selection criteria 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, the description carries the full burden of explaining behavior, but it only states that a report is generated. It does not disclose whether the tool reads files, runs analysis, requires prior outputs, has side effects, or how the report is delivered.

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 short, but it is under-specified rather than appropriately concise. It lacks the front-loaded scoping and parameter context needed to be useful for a tool with five parameters, three of which are required.

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 no annotations, 0% schema description coverage, and no parameter explanations, the description is incomplete for an agent attempting to invoke the tool correctly. The output schema provides some return-value context, but the input meaning and integration workflow context remain unexplained.

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% and the description does not explain any of the five parameters, including required ones like application_path, source, and target. The description adds no value in helping an agent understand what each parameter means or how to fill it.

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 action ('Generate') and the resource ('a human-readable report'), so the high-level purpose is understandable. However, it does not distinguish this tool from siblings like generate_migration_plan or generate_session_migration_plan, and the modifier 'from the integrated migration workflow' is vague.

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 explicit guidance on when to use this tool versus the many sibling migration tools. The phrase 'from the integrated migration workflow' weakly implies it should be used after workflow integration, but no prerequisites, alternatives, or exclusions are mentioned.

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 provided, so the description carries the full burden of behavioral disclosure. It only restates the planning purpose and does not state whether the tool executes changes, has side effects, requires specific registry state, or returns a plan document. This leaves the behavioral profile almost entirely undisclosed.

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 terse sentence with no filler, which is efficient. However, it is under-specified for a tool with seven parameters and no other documentation, making it more sparse than appropriately structured.

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?

Even though an output schema exists, the description does not explain any required input semantics, usage conditions, or behavioral constraints. With four required parameters, zero schema descriptions, and no annotations, the agent lacks enough context to invoke the tool reliably without additional outside knowledge.

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%, and the description does not explain any of the seven parameters, including required ones like source, target, application, and session_run_dir. The phrase 'session overlay' only loosely maps to session_run_dir and offers no actual 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 identifies a specific action ('Plan a migration') and a distinctive scope ('canonical registry plus one run's session overlay'), which differentiates it from the sibling generate_migration_plan. It is not fully self-contained because 'canonical registry' and 'session overlay' rely on domain knowledge, but the core purpose is understandable.

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 explicit when-to-use guidance, no exclusions, and no mention of alternatives such as generate_migration_plan. The phrase 'plus one run's session overlay' hints at a specific use case, but the agent is left to infer when this tool should be selected over others.

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 available, the description carries the full burden of behavioral disclosure. It states that the tool returns a profile and adds the qualifiers 'validated' and 'local registry,' but it does not explain what validation means, whether permissions are required, whether there are side effects, or how failures manifest.

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 with no filler. The verb and primary object are front-loaded, making it easy 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?

The presence of an output schema covers the return shape, so that is not a critical gap. However, the definition lacks usage guidance and identifier semantics, and there are no annotations to clarify behavioral expectations. For a simple one-parameter retrieval tool, this 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 schema has one required 'identifier' with no description and 0% schema description coverage. The description never explains what kind of identifier is expected (e.g., model name, ID, alias) or its format, leaving the agent to infer meaning solely from the tool name.

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 ('Return') and identifies a concrete resource ('validated local registry model profile'). It is not a tautology and conveys the object and scope, though it does not explicitly distinguish from sibling tools like resolve_model or check_model_lifecycle.

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 about when to use this tool versus alternatives such as check_model_lifecycle, resolve_model, or query_live_pricing. The phrase 'local registry' hints at scope, but there are no explicit conditions, exclusions, or comparisons.

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 provided, so the description carries the full burden of behavioral disclosure. It does disclose that results are 'review-only' and 'bounded', which adds meaningful safety and scope context beyond the schema. However, it does not explain side effects, permissions, failure modes, or behavior when optional inputs like limits or candidate_runs are omitted.

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 verb, output type, key constraints, and input source. It is appropriately concise, though it errs on the side of under-specification rather than excessive 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?

Even though an output schema exists and reduces the need to describe return values, the tool still has three undocumented parameters, no annotations, and numerous closely related sibling tools. The one-sentence description does not provide enough context for an agent to confidently construct a call or choose this tool over alternatives.

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%, and the description does not explicitly map any of the three parameters to their roles. 'Observed regression evidence' loosely suggests the required regression_report, and 'bounded' hints at limits, but this is not enough to compensate for the complete lack of 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 ('recommendations from observed regression evidence'), with useful qualifiers like 'bounded' and 'review-only'. It is not a tautology and gives the agent a clear sense of what the tool produces, though it does not explicitly differentiate itself from closely related siblings such as analyze_regressions or generate_migration_plan.

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 'from observed regression evidence' implies when the tool should be used, and 'review-only' suggests it is for non-mutating review rather than execution. However, there is no explicit when-not-to-use guidance and no mention of alternative sibling tools, so the agent must infer routing from 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?

With no annotations, the description carries the full burden, and 'without editing application files' usefully discloses a key non-destructive behavior. Yet it does not clarify whether the tool returns a contract in-memory, persists anything, validates inputs, or has other side effects, leaving substantial behavioral ambiguity.

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 or redundant phrasing. It is efficient, but its brevity contributes to under-specification, so it does not earn a top score.

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 has five parameters, zero parameter descriptions, no annotations, and only the existence of an output schema without visible detail. The description leaves core input semantics and tool-selection context unstated, so an agent would lack essential information for confident 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 0%, so the description must compensate for the undocumented parameters. It does not explain source, target, application_path, source_platform, or target_platform; the word 'target' in the description is too weak to provide meaningful parameter guidance.

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?

States a specific verb ('prepare') and resource ('target invocation contract'), and adds a meaningful constraint ('without editing application files'). It is distinguishable from generic migration-related tools, though it does not explicitly contrast with siblings like prepare_prompt_migration or define what an invocation contract is.

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 'without editing application files' implies a non-file-modifying preparation context, which gives some usage signal. However, there is no explicit guidance on when to choose this over related siblings such as analyze_invocation or prepare_prompt_migration, and no conditions, prerequisites, or alternatives are stated.

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 behavioral burden. It discloses one important trait: it does not rewrite the prompt. However, it does not explain whether the tool reads external state, produces a file, or has any other 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?

The description is a single, front-loaded sentence with no filler. It communicates the core purpose and a key constraint 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 seven parameters, no annotations, and zero schema/description parameter coverage, the description is not sufficient for reliable invocation. The presence of an output schema reduces the need to explain return values, but the input semantics and workflow context remain under-specified.

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%, and the description adds little parameter-level meaning. The phrase 'prompt migration specification' implies source, target, and prompt are involved, but it does not explain the semantics of the seven inputs or what values are 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?

The description states a specific verb ('prepare') and a specific resource ('a prompt migration specification'), and adds a useful negative constraint ('without rewriting the prompt'). It is clear on its face, though it does not explicitly contrast with sibling tools such as prepare_invocation_migration or generate_migration_plan.

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 no guidance on when to use this tool versus alternatives like analyze_prompt, prepare_invocation_migration, or generate_migration_plan. No conditions, prerequisites, or exclusions are mentioned.

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 behavioral burden. It discloses that the tool does not edit canonical files, which is a meaningful non-destructive guarantee. However, it does not clarify whether the tool reads existing state, produces a persistent proposal, or has other 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?

The description is a single front-loaded sentence with no filler. Every word contributes meaning, and the key constraint ('without editing canonical files') is placed up front where an agent will notice it.

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?

Although an output schema exists and the tool has only one parameter, the description is too sparse for a no-annotation tool. It lacks usage guidance and parameter structure details, leaving an agent to guess how to structure the 'research' evidence and what planning behavior entails.

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% and the only parameter 'research' is an open-ended object with additionalProperties allowed. The phrase 'supplied evidence' loosely maps to this parameter but adds no structural detail about expected fields, format, or nesting, so the description does not compensate for the schema's lack of guidance.

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 ('Plan'), a resource ('registry update'), and a source ('supplied evidence'), with a clear non-editing constraint. It distinguishes the tool as a planning-only action, though it does not explicitly name sibling alternatives to differentiate from.

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 this tool is for proposing changes rather than executing them, via 'without editing canonical files.' However, it gives no explicit guidance on when to use this tool versus siblings like build_session_registry or generate_session_migration_plan, and mentions no 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?

With no annotations, the description carries the full behavioral burden. It usefully states that canonical registry facts are unchanged, but it does not disclose whether the tool performs a network call, has side effects, respects a timeout, requires authentication, or returns pricing data directly.

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 very short and structurally clean, but it is under-specified rather than usefully concise. The phrase 'Opt in' is unclear and does not earn its place because it obscures, rather than clarifies, the tool's actual behavior.

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 presence of an output schema reduces the need to describe return values, but the tool still has two undocumented parameters and performs a live external inquiry without clarifying key behavior. The description is too thin for an agent to confidently select and invoke this tool correctly.

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

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

Schema description coverage is 0%, and the description does not mention either parameter. 'identifier' is required but its meaning, format, and accepted values are left entirely implicit, and 'timeout' has a default of 5 with no units or behavior explained.

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 conveys that this tool is related to OpenRouter pricing and that canonical registry data is not changed, which helps distinguish it from registry-update tools. However, 'Opt in to an OpenRouter pricing inquiry' is vague and does not clearly state that the tool performs a live pricing query or what it returns.

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 explicit guidance on when to use this tool versus alternatives like get_model_profile, compare_models, or estimate_migration_cost. The reader can infer it is for live OpenRouter pricing, but no selection criteria, prerequisites, or exclusions are provided.

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 bears the full burden of behavioral disclosure. It does reveal two key traits: 'hard-filter' (some candidates are excluded) and 'deterministically rank' (output order is reproducible). However, it does not mention whether the tool performs network calls (e.g., for live pricing), whether it mutates any state, or if it requires prior actions like scanning an application. These gaps are notable given the 'include_live_pricing' parameter suggests external 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?

The description is one sentence and front-loaded with the core action, which is efficient. However, it is under-specified to the point of being unhelpful. It is not bloated, but it sacrifices substance for brevity, making it inadequate for conveying necessary context.

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 10 parameters, no schema descriptions, and no annotations, the description is severely incomplete. An agent cannot determine what constitutes a 'compatible' model, how ranking is computed, or what inputs are expected. The presence of an output schema mitigates some return-format concerns, but the input side remains opaque. The description would need to explain parameter semantics and usage context to be minimally 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 0%, so the description must compensate by explaining the 10 parameters. It does not mention a single parameter, their allowed values, or their interplay. An agent cannot infer what 'region', 'platform', 'min_context_window', or 'required_capabilities' mean beyond their names. This is a critical failure for a tool with this many 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 a specific action ('Hard-filter and deterministically rank') applied to a resource ('compatible registry models'). It distinguishes itself from siblings like 'compare_models' by focusing on recommendation rather than comparison, and from 'resolve_model' by implying a set-level operation rather than a single lookup.

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 like 'compare_models' or 'generate_migration_plan'. There are no explicit conditions for selection, no exclusions, and no mention of prerequisites (e.g., whether a source model is required). The purpose alone implies a use case, but the description offers no decision support.

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 provided, so the description carries the full burden of behavioral disclosure. It implies a read-oriented lookup and that platform context is optional, but it does not state side effects, error behavior, canonicalization semantics, or what occurs for an unresolvable identifier.

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 with no filler, and the core 'registry identifier' is front-loaded. It earns its place word-for-word, though the brevity borders on under-specification; content gaps are accounted for in other dimensions.

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 three undocumented parameters, no annotations, and a crowded sibling set, this description is not complete enough for confident invocation. Endpoint is unresolved, output semantics are not summarized, and the tool is not positioned against alternatives. A rich output schema could compensate, but the description itself leaves too much implicit.

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 for the undocumented parameters. It adds some meaning by identifying 'identifier' as a registry identifier and marking 'platform' as optional context, but it leaves 'endpoint' completely unexplained and provides no format or value guidance for any parameter.

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 verb/resource pair ('resolve ... registry identifier') and notes optional platform context, so it is not a tautology. However, 'resolve' is ambiguous—it could mean lookup, canonicalization, disambiguation, or version resolution—and no sibling differentiation is offered. Among tools like get_model_profile, compare_models, and propose_registry_update, an agent cannot tell what this tool uniquely resolves.

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 about when to use this tool versus any of the many related sibling tools. The description mentions no exclusions, prerequisites, or preferred scenarios, leaving the agent to infer use 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 provided, the description must carry the full behavioral disclosure burden. It does add one useful behavioral fact—that the tool uses user-owned local provider credentials—but it does not disclose side effects, required authentication setup, execution behavior, or what the tool returns. This is only marginally more informative than a bare operation statement.

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, and the credential detail is relevant to execution. However, it is terse to the point of ambiguity—'Run source and target' does not clearly communicate the operation, so the conciseness comes at the cost of necessary clarity.

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?

This is a complex tool with three required nested object parameters, no annotations, no schema descriptions, and an output schema. A single vague sentence is insufficient for an agent to know what suite, source_config, and target_config should contain, how credentials are provided, or what effects the run has. The description is far from 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 0%, and the description adds almost no parameter meaning. 'Source and target' vaguely maps to source_config and target_config, but the suite parameter is entirely unaddressed, and none of the three nested object structures are explained. The description fails to compensate for the opaque 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 states a specific action ('Run source and target') and a relevant condition ('with user-owned local provider credentials'), but it never explicitly says it runs a migration eval or what 'source and target' refer to. It relies heavily on the tool name for meaning and does not clearly differentiate from siblings like generate_eval_suite or compare_outputs.

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 about when to use this tool versus alternatives. The phrase 'user-owned local provider credentials' implies one usage context, but there is no explicit when-to-use instruction, no exclusion criteria, and no mention of sibling tools or prerequisites such as an eval suite existing.

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 says 'Scan', which suggests a read-only analytical operation, but it never explicitly states that the tool does not modify files, whether it requires network access, or what happens for invalid paths or non-Python directories. With no annotations to cover the safety profile, the description carries the full burden and falls short.

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 with no filler. The action, target, and result are all front-loaded, and every word contributes useful 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?

The tool is simple, with one parameter and an output schema available, so the description does not need to explain return values. However, given no annotations and unclear path semantics, the description is not fully complete. It adequately conveys the core operation but leaves behavior and parameter details ambiguous.

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?

There is only one parameter, 'path', and schema description coverage is 0%. The description infers that the path points to a local Python application, but it does not clarify whether the path should be a directory, a file, a project root, or what format is expected. It adds minimal meaning beyond the bare string type.

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 ('Scan'), a clear resource ('a local Python application'), and a specific outcome ('a normalized coupling inventory'). This clearly distinguishes it from sibling migration and validation tools, which focus on generating plans, research requests, or evaluations rather than scanning code into an inventory.

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 intended use case is implied: use this when you need to scan a local Python application and produce a coupling inventory. However, the description does not explicitly say when it should or should not be used compared to the many sibling tools, nor does it mention any prerequisites or exclusions.

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 of behavioral disclosure. It states the tool checks coverage, but does not explain what 'covers' means, whether the check is read-only, what criteria are used, how failures are reported, or what side effects may occur.

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 with no filler, and the key verb and target are front-loaded. It is appropriately concise for the limited content it provides.

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?

Despite the presence of an output schema, the tool has two nested object parameters with no schema-level documentation and no annotations, yet the description offers only a high-level 'check coverage' statement. An agent would not know how to structure the inputs, interpret success, or understand the check's semantics in relation to surrounding research-validation tools.

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%, and the schema only lists 'review' and 'research' as generic objects with additionalProperties allowed. The description maps these names to conceptual meanings ('evidence review' and 'research artifact'), which adds a little value, but it does not explain expected fields, shapes, or constraints needed to call the tool correctly.

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 clear verb ('Check') and names the specific resource ('independent evidence review') and target ('research artifact'), so the tool's core purpose is understandable. It does not explicitly distinguish itself from sibling 'validate_research_result', but its focus on review coverage is reasonably distinct.

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 the tool is used when an independent evidence review exists and needs to be checked against a research artifact, but it gives no explicit guidance on when to choose this tool over siblings like validate_research_result or build_research_consensus. No exclusions, prerequisites, or alternative routing are provided.

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 for behavioral disclosure. It only says the validation is static, which hints at non-destructive analysis, but it does not describe registry access, failure behavior, or whether any state changes occur.

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 with no filler, front-loading the action and scope. Every word contributes to the tool's identity.

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 too sparse for a tool with four parameters, two of them undocumented, and no annotations. Even with an output schema, the agent is left guessing about source_path, target_platform, and the precise validation 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?

Schema description coverage is 0%, so the description must clarify all parameters. It only hints that 'prompt' maps to prompt assumptions and 'target' maps to registry facts, and it leaves source_path and target_platform 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?

The description names a specific verb ('validate') and resource ('prompt assumptions against target registry facts'), which distinguishes it from sibling validation tools like validate_research_result and validate_evidence_review. 'Statically' also narrows the mode. It could be more explicit about what qualifies as a prompt assumption, so it is not 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 is given about when to use this tool versus validate_research_result, validate_evidence_review, or analyze_prompt. The word 'statically' implies a non-runtime check, but no conditions, prerequisites, or alternative tool mentions are provided.

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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It discloses that the operation is 'deterministic' and acts as a 'gate,' but it does not explain whether validation failures block execution, whether the tool has side effects, what permissions are needed, or how results are returned. This is comparable to a mutation tool that never states its 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?

The description is a single sentence with no filler and front-loads the core action. The phrasing 'deterministic scope/policy gate' is jargon-heavy but compact and arguably earns its place by hinting at the validation rule type.

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 two opaque nested parameters, no annotations, and no parameter documentation, the description is not complete enough for confident invocation. The existence of an output schema reduces the need to describe return values, but the description still leaves the input contract and gate semantics unexplained.

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%, and the description does not compensate. It does not explain that 'research' is the artifact being validated or that 'request' carries the scope/policy context. Both parameters are opaque nested objects with additionalProperties true, so the agent has no semantic anchor for what to provide.

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 ('Run') and a specific resource ('one research artifact'), and 'deterministic scope/policy gate' conveys a clear validation function. It does not explicitly differentiate from sibling tools like validate_evidence_review, but it is not tautological and is more specific than a vague summary.

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 no guidance on when to use this tool versus validate_evidence_review, validate_prompt, or other sibling validators. There is no mention of prerequisites, intended workflow position, or exclusion criteria. The only contextual hint is 'over one research artifact,' which is a scope statement rather than usage guidance.

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