Tetrees AI

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

The phrase 'append it to this owner only' hints at a side effect, and 'deterministic growth gate' suggests validation, but the description does not disclose failure modes, idempotency, ownership checks, or confirmation semantics. With no annotations, the description carries the full burden, and it is largely opaque.

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 but is convoluted and repetitive, mixing 'Tetrees Agent' and 'provider-free portable normalization' without clarity. It is compact but not accessible, and the structure does not help an agent parse the intended workflow.

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

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

Given the absence of an output schema and annotations, the description leaves out critical context such as expected inputs, return values, error conditions, and how this action relates to the growth proposal lifecycle. The tool cannot be invoked confidently based solely on this description.

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

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

The schema covers only 25% of parameters with descriptions, and the description does not explain sequence, confirmation, or normalization in a meaningful way. The 'normalization' enum values 'tetrees' and 'portable' are not elaborated, and the required confirmation constant is never addressed in prose.

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 vague, jargon-heavy verbs like 'normalize', 'run the deterministic growth gate', and 'append it to this owner only' without clearly stating that this tool accepts a proposed growth item. The tool name provides some signal, but the description alone is insufficient to understand the core action.

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

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

There is no guidance on when to use this tool versus the many sibling tools such as propose_ai_pack_growth, select_ai_pack_growth_version, or list_ai_pack_growth. No prerequisites, sequencing, or alternative selection criteria 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?

There are no annotations, so the description carries the full burden of disclosing side effects. It says 'Record' but does not state whether acceptance is idempotent, irreversible, or what happens if terms were already accepted.

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 concise sentence conveys the core action and preconditions without redundancy or irrelevant detail.

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

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

For a simple consent-recording tool with no output schema, the description covers the essential what and when. It omits return or error details, but those are not required given the lack of an output schema and the tool's simplicity.

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

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

The single confirmation parameter is self-explanatory through its const value, but the description adds no explanation and the schema provides no parameter description. Since schema coverage is low, more explicit guidance would be better.

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 title and description clearly indicate this tool records acceptance of seller terms for AI Packs. The phrasing 'current account agreement' is slightly awkward, but the intended action is unmistakable.

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 states the tool is required before creating, uploading, auditioning, or publishing a pack, giving clear preconditions. It does not mention alternatives, but none are apparent for this consent action.

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 discloses the key trait 'revocable' and restricts to 'published free pack', but it does not specify what happens if the pack is not free/published, whether the operation is idempotent, or what the response contains. Some behavioral context is present but not comprehensive.

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

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

A single sentence, front-loaded with the core action, no filler words. It conveys the essential purpose and differentiators 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?

For a one-parameter tool, the description covers the essential purpose but omits error conditions and return behavior. It lacks detail on conflicts (e.g., existing entitlement) and does not clarify what 'revocable' means in terms of API behavior. Adequate for a simple operation but not fully complete.

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

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

Schema description coverage is 100%, so the schema already documents productId. The description adds only the implicit constraint that the product must be a published free pack, which is not a parameter-level detail. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a precise verb ('Create') and resource ('revocable entitlement') and adds qualifiers ('published free pack', 'without Stripe') that sharply distinguish this tool from siblings like accept_ai_pack_terms or publish_ai_pack. It is unambiguous about the tool's core action.

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 Stripe' implies this is the alternative path when Stripe is not involved, giving context for when to choose this tool. It does not name a specific sibling, but the condition is clear enough for an agent to infer the intended use case (free, published packs bypassing payment).

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 burden of explaining side effects. It mentions the need to accept terms and that free drafts avoid Stripe Connect, which are useful preconditions. However, it does not state what happens to existing drafts, whether the draft becomes visible, or if any other state is modified, so transparency is partial.

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 only two sentences, yet it conveys the key purpose, ownership, required content, and payment-related exceptions. It is well-structured, directly to the point, and contains no redundant or verbose phrasing.

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 does not mention the return value or output of the tool, and the absence of an output schema leaves the agent without expectations. It also fails to explain the nested structure of the 'listing' object, which is complex and could benefit from clarification, making the description incomplete for a tool of this complexity.

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

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

The schema provides no parameter descriptions, and the tool description only adds minimal guidance by referencing 'buyer guide' and 'two concrete example uses'—implicitly mapping to the listing fields and exampleUses array. It fails to explain the purpose of individual parameters like 'capabilities', 'models', or 'priceUsd', leaving the agent to guess from names and constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Create' and a specific object 'owner-bound AI Pack listing' with required contents (buyer guide, two concrete example uses). It distinguishes this from a general draft by specifying ownership and completeness, making the tool's purpose unambiguous.

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

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

The description gives preconditions (accept terms, no Stripe Connect for free drafts) but does not mention any alternative tools or when to prefer this over others like 'update_ai_pack_draft' or 'publish_ai_pack'. It lacks explicit guidance on when to use this tool versus sibling tools, leaving the agent to infer context 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?

The description discloses that the result is a short-lived, entitlement-gated URL rather than a direct file stream, which is important behavioral information. However, it does not mention error conditions, authentication requirements, or whether any state changes occur. Since no annotations are provided, this level of transparency is adequate but not thorough.

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 superfluous words. It efficiently conveys the core action and output without extraneous details.

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

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

For a simple tool with one parameter and no output schema, the description gives the essential outcome (a URL) but omits context such as how the URL should be used (e.g., HTTP GET) or whether it expires immediately. The description is sufficient for basic invocation but lacks some operational context that would be helpful.

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 only parameter, productId, has a schema description ('Tetrees AI Pack product id') that merely restates the parameter name without adding meaningful semantics. With 100% schema coverage, the baseline is 3, and the tool description does not enhance the parameter meaning further.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description precisely states the tool's function: returning a short-lived, entitlement-gated URL for the signed .taip envelope. The verb 'return' and the specific resource type make the purpose unambiguous, and it clearly differs from sibling tools like run_ai_pack or publish_ai_pack.

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 its siblings (e.g., when to choose download_ai_pack over get_ai_pack_report or run_ai_pack). There is no mention of prerequisites, such as ownership or entitlement requirements, or conditions under which this tool should be preferred.

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 transparency burden. It discloses local credential handling and the write-confirmation requirement, but it does not describe potential side effects, error behavior, or whether the method may read or modify external state beyond the write confirmation.

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 concise and well-structured, using two sentences to communicate the core purpose and key constraints without redundant 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 tool has no output schema and no annotations, so the description must provide sufficient context. It explains execution modes, local credential handling, and write confirmation, but omits return format, failure modes, and parameter-level details, leaving some gaps for an agent to infer.

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 only 40%, with productId and writeConfirmation described while methodId, extensionId, and arguments are left undocumented. The description mentions 'one method from an owned Pack' but does not clarify the roles of methodId, extensionId, or the arguments object, so it does not compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: executing one method from an owned Pack, and enumerates the supported execution modes (HTTPS API, MCP server, local-skill child process). It is specific about the resource and scope, though 'client extension' is not explicitly defined relative to 'Pack'.

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 useful behavioral guidance: configuration and credentials remain local, and write methods require an exact one-call confirmation. However, it does not explicitly explain when to choose this tool over sibling tools such as run_ai_pack or prepare_local_ai_pack_run.

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 clearly indicates a read-only operation ('Read') and mentions privacy behavior ('without exposing them to buyers'). It does not detail error handling or permission requirements, but the core side-effect-free nature is adequately conveyed.

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

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

The description is a single, compact sentence that leads with the action and object. No redundant words or filler. It is well-structured and immediately understandable.

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 fully explains what the report contains ('actionable owner-only failures and next actions') and the privacy constraint. Given the simple one-parameter tool and no output schema, no additional context is necessary for correct usage.

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 sole parameter productId is described as 'Tetrees AI Pack product id,' which clearly identifies its meaning. The UUID format is specified. The description could add context about whose product ID (owner-specific) but given full schema coverage, the parameter semantics are sufficiently clear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: reading owner-only failures and next actions. It explicitly distinguishes itself from public reports by noting it avoids exposing information to buyers, which makes its specific role unambiguous.

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

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

The description implies when to use this tool (for private owner feedback) and contrasts it with buyer-exposed information, effectively signaling the alternative (get_ai_pack_report). However, it does not explicitly name the alternative or provide explicit 'use this when' instructions, so it falls slightly short of full guidance.

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

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

With no annotations, the description carries the full burden for behavior. The verb 'Read' clearly indicates a non-mutating, read-only operation, which is the primary behavioral trait. No side effects or destructive actions are suggested.

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 redundant wording. It directly states the resource, action, and scope without unnecessary detail.

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

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

The description is sufficient for a simple read operation, but it omits an output description and does not clarify how this report differs from the similarly named get_ai_pack_private_report. Given the sibling tools, this could leave an agent uncertain about which report is appropriate.

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 one parameter, productId, and its schema description clearly identifies it as a Tetrees AI Pack product ID. The tool description adds context that the product must be a published pack, making the parameter's role clear.

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 that this tool reads Agent AVCP gates and scores for a published pack, using the specific verb 'Read'. It distinguishes the report from drafts by mentioning 'published pack', though the word 'buyer' is slightly ambiguous.

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 guidance is given about when to use this tool versus alternatives such as get_ai_pack_private_report or get_ai_pack_submission_readiness. The description implies published packs only, but does not state prerequisites, use cases, or 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?

There are no annotations, so the description bears the full burden of disclosing side effects or safety. The verb 'Return' and the getter-style name imply a read-only operation, but the description does not explicitly state that no state changes occur or mention authorization or rate-limit considerations. This leaves some ambiguity for an agent deciding whether invocation is safe.

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

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

The description is a single, compact sentence that front-loads the verb and enumerates the returned items without redundant phrasing. Every term contributes to the tool's purpose. It is appropriately sized for the simple one-parameter interface.

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 lists all major categories of returned data (skills, attachment policy, extensions) and situates the call before a run, which is enough for an agent to select this tool. Because there is no output schema, the description partially substitutes by naming the content areas. It does not specify output format or field structure, but this is not necessary for choosing the tool.

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

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

The only parameter, productId, is fully described in the schema as 'Tetrees AI Pack product id', and the runtime-profile context implies it identifies the pack. Since schema coverage is 100%, the baseline applies. No additional parameter behavior or format detail is added beyond the 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 clearly states the tool returns a runtime profile with three specific categories: hosted skills, attachment policy, and user-controlled MCP/API extensions. The title reinforces the execution-skills inspection purpose, and the 'before a run' phrase helps distinguish it from execution-oriented siblings. It does not explicitly name alternative tools, but the purpose is unambiguous.

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

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

The description gives a temporal cue ('before a run') that indicates when this lookup is appropriate, but it does not explicitly compare with siblings like get_ai_pack_report or prepare_local_ai_pack_run. No alternative conditions or exclusions are provided. This is adequate but not explicit guidance.

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

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

Annotations are absent, so the description bears full responsibility for behavioral disclosure. It describes the return content but does not state whether the operation is read-only, has side effects, or requires specific permissions. For a 'get' tool it is likely safe, but that is not disclosed.

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 purpose ('Return missing TAIP, metadata, and imagery requirements') and then adds the key value ('with exact next actions'). There is no fluff or redundancy.

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

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

For a simple tool with one parameter and no output schema, the description gives a high-level summary but omits details about the return structure (e.g., whether it returns a list, object, or plain text) and when exactly to use it. It is adequate but leaves gaps that could matter for an agent deciding how to act on the result.

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

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

The single parameter productId is fully described in the schema (100% coverage) as 'Tetrees AI Pack product id'. The description adds no additional meaning about the parameter, such as format constraints or how it is used. With high schema coverage, the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Return' with a clear resource: missing TAIP, metadata, and imagery requirements. It clearly indicates the tool evaluates submission readiness. This is distinct from any sibling tool; none of the siblings mention readiness checks or requirements, so the agent can easily differentiate it.

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. Siblings like submit_ai_pack_for_audition and publish_ai_pack exist, but the description does not state that this tool should be called before those or as a prerequisite. The context is implied by the name but not explicitly 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 provided, so the description carries the full burden. The verb 'List' implies a read-only operation, but the description does not explicitly state that it has no side effects, does not require authentication, or mention potential rate limits. This is a minor gap given the obvious read-only nature.

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 lists the key content elements without any redundancy or fluff. It is well-structured and easy to parse.

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

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

Given the tool's low complexity (no parameters, no output schema), the description adequately covers the essential context by enumerating the data it returns. It does not specify the output format, but that is a minor omission for such a simple list operation.

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

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

The tool has zero parameters, and the schema coverage is trivially 100%. The baseline score for 0 parameters is 4, and there is no additional parameter information to provide or clarify.

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 'List' and clearly identifies the objects being listed: OpenAI, Claude, Z.AI models, pricing, capabilities, BYOK support, and sample Point quotes. This fully clarifies the tool's purpose with no ambiguity.

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

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

The description provides clear context for when to use the tool: when needing to see available models and pricing. It does not explicitly state when not to use it or compare with alternatives, but the context is sufficient for an agent to infer the appropriate use case.

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 disclosing behavior. It conveys a read-only listing action and notes a privacy boundary, but it does not mention potential errors, permissions, return format, or whether any side effects occur. Adequate but not fully transparent.

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 that efficiently conveys the tool's purpose and key exclusions without unnecessary detail.

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

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

Given the tool's low complexity and lack of an output schema, the description sufficiently enumerates what will be returned: checkpoints, active checkpoint, usage, and limits. It could mention ordering or pagination, but these are minor omissions for this simple listing tool.

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

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

The schema covers the single productId parameter with a description and UUID format, so baseline coverage is complete. The description adds little beyond the schema, though it does restate that productId identifies the AI Pack.

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 what the tool does: lists growth checkpoints, the active checkpoint, hosted slot/byte usage and limits. It also explicitly distinguishes itself by noting it does not expose private memory contents, which helps differentiate it from related report tools.

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

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

The description does not explicitly state when to use this tool versus alternatives. It hints that private memory content is excluded, but it does not name sibling tools or provide conditions for selection, leaving usage guidance largely implicit.

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 indicates a read-only operation ('list') with no side effects. While there are no annotations, the wording is consistent with a safe, non-mutating action, providing adequate 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 a single, concise sentence that fully conveys the tool's function without unnecessary detail or repetition.

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 sufficient for a parameterless read-only list operation. It states what is listed (owned packs) and the scope (account). It does not specify output format, but that is not critical for basic usage.

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

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

The tool has no parameters, so there is nothing to explain. The description correctly reflects this, and no additional parameter guidance is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists purchased, claimed-free, and seller-owned packs for the current account. It uses a specific verb ('list') and defines the scope, making its purpose unambiguous.

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

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

The description implies when to use this tool (when needing owned packs) but does not explicitly contrast it with sibling tools like search_ai_packs. It lacks direct guidance on when to prefer this over 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 burden. It discloses a critical behavior: the tool returns a plan and does not execute client extensions on hosted servers. This signals that it is a planning/preparation operation, not a direct execution. It does not mention side effects or permissions, but the core non-execution trait is clearly stated.

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 with the core action front-loaded. The second sentence adds an important constraint (no server-side execution) without redundancy. Every word earns its place.

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

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

The description conveys the primary purpose and a key constraint, but with no output schema, it does not describe the structure of the returned execution plan or how it should be consumed. It also omits details about required parameters and the meaning of 'Agent-AVCP-auditioned'. For a tool with 4 parameters and 2 required, the description is serviceable but leaves gaps in usage understanding.

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 50%, leaving task, productId, and selectedExtensionIds undocumented. The description adds only generic context ('connecting to selected local skills, MCP tools, resources, prompts, or HTTPS APIs') which maps loosely to selectedExtensionIds but does not explain the format or purpose of the required parameters (productId, task) or the approvedWriteMethods array. The description fails to compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action: 'Return a host-readable execution plan' for connecting this Pack to explicitly selected local extensions. It also distinguishes itself from siblings like execute_client_extension by clarifying that Tetrees does not execute client extensions on hosted servers. This makes the tool's purpose unmistakable.

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

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

The description implies usage for local, user-selected runs ('explicitly selected, Agent-AVCP-auditioned local skills') and hints at a prerequisite (auditioned extensions). However, it does not explicitly name alternatives or state when NOT to use this tool versus run_ai_pack, execute_client_extension, or quote_ai_pack_audition. The guidance is implied, not explicit.

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 explicitly states that it does not mutate the pack, which addresses a key side-effect concern. It also indicates it creates a reviewable delta, but it does not mention whether the run or proposal state is otherwise changed, or error conditions. With no annotations, this is a moderate level of 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 two short sentences with no redundant or promotional language. It efficiently conveys the operation and side-effect profile.

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 two-parameter action with no output schema or annotations, the description covers the core operation and side-effect effectively. It lacks explicit mention of the response shape or next steps, but the operation is simple enough that the description is nearly 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 fields are runId and proposalIndex, and the description only implicitly references them ('successful run', 'proposal'). It does not explicitly define the UUID run identifier or the zero-based index and range semantics, though the names and schema constraints make them inferable.

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 ('Select a proposal'), the required context ('from a successful run'), and the primary outcome ('creates a reviewable delta'). It also clarifies that the pack is not mutated, making the purpose unmistakable.

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

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

The description implies usage for reviewing a proposal before acceptance, but it does not explicitly contrast with sibling tools such as accept_ai_pack_growth or list_ai_pack_growth. The condition 'successful run' is a prerequisite signal, but no when-to-use or when-not-to-use guidance is given.

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

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

The description implies a state transition (publishing a pack) but does not disclose side effects such as making the pack publicly visible, whether the action is reversible, or if it triggers notifications. No annotations exist, so the description carries the full burden and only partially addresses behavior.

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

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

The description is concise, using two sentences to convey the primary condition and the paid-pack exception. It is well-structured and does not include unnecessary detail.

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

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

The description covers the essential trigger (AVCP gates) and a key dependency (Stripe Connect for paid packs), but omits information about the publish result, error conditions, or relationship to the sibling 'submit_ai_pack_for_audition' tool. Given the tool's moderate complexity (publish action with variant logic), the description is adequate but not fully comprehensive.

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 descriptions for both parameters ('Tetrees AI Pack product id' and the confirmation constant), but the description does not add further context on why the confirmation is required or what happens if the ID is invalid. Schema coverage is 50% (both parameters have descriptions), so the baseline is met but no extra value is added.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Publish') and the resource ('the exact current version') with a condition ('after every mandatory Agent AVCP gate passes'). It is distinct from siblings like 'submit_ai_pack_for_audition' or 'create_ai_pack_draft', though it does not explicitly contrast 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?

It provides the core condition for when to use the tool (after AVCP gates pass) and a special requirement for paid packs (Stripe Connect). However, it does not explicitly state when not to use it or mention alternatives, leaving some implicit guidance.

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

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

The description discloses the BYOK exception (zero model points) and indicates that the tool returns a reservation, implying a read-like quoting action. Yet it does not state whether the reservation holds funds, whether the operation is entirely side-effect-free, or what the output structure contains, especially given the absence of annotations.

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

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

The description is concise and front-loaded, using two short sentences with no filler or redundancy. It efficiently conveys the primary purpose and the key BYOK variant, though the brevity comes at the cost of needed detail.

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

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

Given the tool's moderate complexity (7 parameters, no output schema, no annotations), the description omits essential context such as how the worst-case reservation is calculated, how to interpret the returned quote, and how parameters like growthVersion or enabledSkills affect the result. The agent would need to infer or guess major operational details.

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

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

With only 29% schema coverage and no parameter explanations in the description, the agent receives no meaningful guidance on what productId, model, fundingMode, enabledSkills, or maxInputTokens/maxOutputTokens actually control in the quote calculation. The description fails to compensate for the sparse schema, leaving most parameters semantically 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 clearly states the tool's core function: obtaining a worst-case Point reservation before platform-funded inference, with a special note that BYOK yields zero model points. The title 'Quote an AI Pack run' reinforces this purpose, though it does not explicitly differentiate from the sibling 'quote_ai_pack_audition'.

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 'before using platform-funded inference' provides limited contextual guidance for when to invoke the tool. However, it does not mention when to prefer this tool over alternatives such as quote_ai_pack_audition or prepare_local_ai_pack_run, leaving selection largely to the agent's 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?

No annotations are present, and the description does not disclose side effects, permissions, read-only status, or any behavioral traits. The tool could be mutating or querying, but nothing is revealed.

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 brief but not concise in a helpful way; it sacrifices clarity for brevity. It is a single sentence that omits critical context, making it more cryptic than succinct.

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 highly incomplete, lacking any context about what the tool does, its inputs, outputs, or relationship to sibling tools. A user would have no idea how to invoke or interpret 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?

The single parameter 'productId' has a description 'Tetrees AI pack product id', which identifies its type but does not clarify how it is used in the context of quoting or auditioning. The overall ambiguity of the tool undermines the parameter's meaning.

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 exact version-bound Point quotes and Agent AVCP deliverables' is cryptic and fails to specify what 'Point quotes' or 'AVCP deliverables' are. It does not clearly state the tool's function or how it differs from siblings like 'quote_agent_run' or 'run_ai_pack_audition'.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of conditions, prerequisites, or typical scenarios, making it impossible to infer appropriate usage.

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

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

Discloses that unfunded runs are stateless, ownership changes BYOK/growth/download behavior, and local files remain request-scoped. It does not explicitly state whether the run is billed, whether growth is saved, or whether other side effects 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?

Two dense sentences with no fluff or repetition; the most important action is front-loaded and each clause carries 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?

With 9 parameters and no output schema, the description does not mention return format, error behavior, streaming, or authentication. It is sufficient for a high-level run action but not fully complete for a caller.

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?

Adds useful meaning for fundingMode, growthVersion, and attachmentPaths through the BYOK/growth/request-scoped references. However, model, prompt, and token-limit parameters are left entirely to their schema constraints, and enum values are not expanded.

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 the specific action 'Run a Tetrees AI Pack' and clarifies the pre- vs post-acquisition modes. It does not explicitly distinguish this from the sibling run_ai_pack_audition, but the core purpose is unambiguous.

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

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

Gives some contextual guidance about Points-funded preview, BYOK, and saved growth, but never says when to prefer this tool over run_ai_pack_audition, quote_agent_run, or prepare_local_ai_pack_run. The alternative conditions are left implicit.

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 disclose behavior. It indicates the action is gated and runs multiple checks, but it does not state whether the operation is read-only, what side effects occur, whether it publishes or accepts anything, or what the return behavior is. This is only partially transparent.

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

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

The description is a single, compact sentence that front-loads the verb and key scope. It avoids redundancy and extra prose, though the dense jargon ('Point confirmation', 'AVCP') reduces clarity but not structural efficiency.

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

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

The description mentions the gate categories and a confirmation requirement, but it omits essential operational context: what the audition returns, whether it changes state, how it relates to quoting or submission, and what happens if gates fail. Given the complexity and lack of output schema, this is incomplete.

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 only 20%: only productId has a description. The description does not compensate for the undocumented parameters (tier, confirmation, expectedPoints, expectedVersion), leaving their meaning and relationship to the operation unexplained beyond raw JSON schema constraints.

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 ('Run') and a concrete resource ('Agent AVCP audition') with a clear list of gate types (integrity, model, regression, memory-isolation, injection, growth, cost). The phrase 'after explicit Point confirmation' adds a prerequisite, though the acronym 'AVCP' and 'Point confirmation' are unexplained.

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 such as quote_ai_pack_audition, run_ai_pack, submit_ai_pack_for_audition, or prepare_local_ai_pack_run. The description only states a prerequisite ('after explicit Point confirmation') but does not clarify selection criteria or ordering.

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 verb 'Search' implies a read-only operation, but the description does not explicitly state side effects, permissions, rate limits, or that no data is modified. With no annotations, the description carries the burden of behavioral transparency and only partially meets it.

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 redundant or extraneous information. It is appropriately sized for the tool's simple purpose.

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

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

The description provides the essential search intent and parameters, but it does not mention what the response contains, how many results are returned, or any filtering semantics beyond the broad 'task or capability'. For a simple search 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 phrase 'by task or capability' gives some semantic hint about the `query` parameter, but neither `query` nor `limit` is explicitly described. The schema constraints (maxLength, max/min) are not explained, and `limit` behavior is left entirely to inference.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Search') and the resource ('published agent-asset exchange'), with the search dimension ('by task or capability') specified. It lacks a bit of precision about what kind of results are returned, but the core purpose is unambiguous.

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

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

There is no guidance on when to use this tool versus any of the many sibling tools, such as list_owned_ai_packs or list_agent_models. No conditions, exclusions, or alternative recommendations 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?

The description discloses a key behavioral guarantee ('selection never rewrites the seller Pack') and indicates a state-changing operation ('set this account's default'). However, it does not mention the required confirmation mechanism or potential failure modes. Since no annotations are provided, the description carries the full burden but is incomplete.

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 concise, using two sentences to convey purpose, a special case, and a safety guarantee. Every clause adds value; there is no fluff or repetition.

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

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

For a simple tool, the description covers the main action and an important side-effect. However, it does not explain why confirmation is required, what the output looks like (no output schema), or any postconditions. Given the consequential nature of changing a default, more context would be helpful.

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 minimal descriptions (e.g., 'Tetrees AI Pack product id', 'sequence', 'confirmation'), but the tool description adds meaningful context for 'sequence' (0 means base). The 'confirmation' parameter is not explained beyond its const value, and 'productId' remains a simple identifier. The description partially enriches the schema but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the core action ('Set this account's default hosted intelligence checkpoint'), specifies the resource ('for an owned Pack'), and distinguishes from the sibling by noting it 'never rewrites the seller Pack.' This is a specific verb-resource pairing with clear scope.

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

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

The description gives a specific usage instruction ('Use sequence 0 to return to the signed base Pack') but does not explicitly mention when to prefer this tool over alternatives like propose_ai_pack_growth or list_ai_pack_growth. The guidance is present implicitly, not explicitly.

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

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

No annotations are provided, so the description carries full responsibility for disclosing side effects. It mentions the queue is immutable, hinting at irreversibility, but does not explicitly warn about consequences, permissions, or the confirmation requirement, which is critical for a mutation operation.

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, clear sentence with no redundant words. It efficiently conveys the action, condition, and destination.

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 explains the precondition and action but does not mention expected outputs, error states, or what happens if readiness fails. Given the confirmation parameter and irreversible nature, more context about the submission result or validation would improve completeness.

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

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

The schema covers two parameters; productId has a brief description, and confirmation is defined via a const but lacks an explicit explanation. The tool description adds no additional parameter context, resulting in moderate schema coverage with minimal elaboration.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (move), the object (complete owner-bound draft), the destination (immutable Agent AVCP queue), and the precondition (after readiness passes). This distinguishes it from related tools like publish_ai_pack or run_ai_pack_audition.

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 a clear condition for use: after readiness passes. However, it does not explicitly compare with alternative tools (e.g., publish_ai_pack) or state when not to use it, leaving some inference to the agent.

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

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

The description discloses a key behavioral guarantee—that pack versions are immutable and never overwritten—which is important for an agent to understand side effects. It does not cover permissions or other side effects, but the core behavioral contract is clearly stated.

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 exceptionally concise, consisting of two short sentences that immediately convey the action and scope. It is well-structured and front-loaded with the verb and object, with no redundant 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?

Given the complexity of the schema (8 parameters, a nested listing object, and no output schema), the description provides only a high-level summary. It clarifies the nature of the update but does not elaborate on the extent of 'public metadata' or any additional effects, leaving some ambiguity for the agent.

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?

Only productId has a schema-level description, and the tool description itself provides no explanation of any parameter semantics. With 8 parameters and no annotations, the description fails to clarify what values or combinations are expected for the fields like tags, listing, or priceUsd.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Update' and the resource 'seller-owned public metadata', making the primary purpose unambiguous. It also distinguishes the tool from siblings like create or publish by explicitly noting that immutable pack versions are never overwritten.

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 when to use the tool (for metadata updates only) and when not to (never for version overwrites), but it does not explicitly name alternative tools or provide decision criteria. Without annotations, the guidance is present but not fully explicit.

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 discloses that the tool has a side effect (committing an immutable higher version), indicating state change. However, it does not mention authentication, idempotency, failure modes, or other behavioral details. Since no annotations are provided, this is the only 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 a single, well-structured sentence that lists steps in logical order: read, transfer, commit. It is concise, front-loaded with the primary action, and contains no redundant 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?

The description omits information about the changelog parameter, output format, and error handling. For a tool with 4 parameters and no output schema, it provides only a basic overview and lacks specifics needed for complete understanding.

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 description adds meaning to packPath (explicit local path) and version (immutable higher version), but it does not address changelog or clarify productId beyond 'product-scoped'. With schema description coverage at only 25%, the description only partially compensates for the missing parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's action: reading a local .taip file, transferring it via a private upload contract, and committing a new version. It distinguishes this from sibling tools like uploading an image or creating a draft.

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

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

The description provides no guidance on when to use this tool over alternatives such as create_ai_pack_draft, publish_ai_pack, or upload_ai_pack_image. No conditions, prerequisites, or comparisons 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. It does not disclose side effects (e.g., replacing existing images), validation rules, authentication requirements, or error behaviors.

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

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

The description is a single, tightly worded sentence with no redundant information. It uses active voice and is directly to the point.

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

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

For a simple upload tool, the description covers the core action and target. However, it omits information about return values, potential errors, and side effects, which may leave an agent without enough context for robust usage.

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 50% (productId described, imagePath not). The description adds the fact that the image is 'local', which helps interpret imagePath, but it does not explain the expected format or constraints for imagePath.

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 specifies the action (upload), the object (one explicit local JPEG, PNG, WebP, or AVIF image), and the destination (seller-owned pack listing). It is distinct from sibling tools like upload_ai_pack.

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 use this tool versus alternatives, nor does it mention prerequisites or conditions. The context is implicit but not stated.

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