aivectormemory

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

No annotations are provided, so the description carries the full behavioral burden. It says nothing about whether saved preferences are merged or overwritten, whether duplicate tags accumulate, what permissions or scope enforcement applies at save time, or what the tool returns. 'Auto' implies no confirmation prompt, but that is the only inferable trait.

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 the imperative directive front-loaded in brackets followed by the resource. Nothing is wasted. It is slightly terse for a tool with behavioral ambiguity, but structurally clean.

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?

No output schema exists, so the description should say more about the result of a save and how it interacts with the retrieval siblings. With zero annotation coverage and only two optional parameters, the definition is minimally adequate but leaves the persistence model opaque.

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 both parameters are already documented (extra_tags, and preferences with scope=user / cross-project semantics). The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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?

Names a specific verb+resource: save (自动保存) user preferences. The purpose is unambiguous on its own. However, it makes no attempt to differentiate from the sibling 'remember', which plausibly stores the same kind of information, so the agent cannot tell the two apart from the description alone.

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

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

Provides an explicit timing directive (must be invoked before every conversation ends), which is more than most tools offer. But it gives no alternatives or exclusions — with siblings like remember and forget, it never says when NOT to use this or how it relates to them, leaving the agent to infer the boundary.

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 behavioral burden. It hints at the single-vs-bulk deletion modes, but for a destructive operation it says nothing about irreversibility, whether deletions can be recovered, or permission requirements. This is a meaningful gap for a tool that removes stored data.

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 short sentence that is well front-loaded with the verb and scope of effect. It earns its place, though the extreme brevity leaves no room for the caution a destructive tool warrants.

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 destructive tool with four parameters, no annotations, and no output schema, the description is incomplete. It omits any discussion of consequences, confirmation expectations, or scope effects that an agent would need before invoking a delete 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?

Schema description coverage is 100%, so the four parameters (tags, scope, memory_id, memory_ids) are already documented in the schema, including the tags/scope interaction. The description adds no syntax or format detail beyond that, so the baseline 3 applies.

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 and resource ('delete one or more memories'), which is unambiguous and distinct from the read-oriented siblings (remember, recall). However, it does not explicitly contrast itself with those siblings, so the agent must infer the inverse relationship from the name alone.

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

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

There is no when-to-use guidance, no prerequisites, and no mention of an alternative tool for related operations. The agent receives only a statement of effect, not context for selecting this tool over remembering, recalling, or tracking.

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 mentions input sources and capabilities but omits critical behavioral details such as whether the tool modifies files, what happens on missing input, or what the output format is. The safety and side effects are unclear.

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 conveys the core functionality efficiently. It is front-loaded with the main purpose and includes key details (source files, multi-language, diff) without unnecessary 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 three optional parameters and no output schema, the description partially covers the needed context. It explains the input sources and general capability but does not specify the return format, behavior of the 'diff' action, or how optional sections are used. More detail would be beneficial.

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?

All three parameters are described in the schema (100% coverage). The description adds value by revealing the source files and the fact that the tool generates content, which is not in the schema. It provides context that helps understand the tool's purpose beyond the parameter 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 clearly states that the tool generates README content from specific files (TOOL_DEFINITIONS/pyproject.toml/STEERING_CONTENT) and supports multi-language and diff comparison. It uses a specific verb 'generate' and identifies the resource 'README', differentiating it from siblings like 'auto_save' or 'graph'.

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 over alternatives. The description does not explain the difference between 'generate' and 'diff' actions or when each is appropriate. There is no mention of prerequisites or context for 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?

With no annotations provided, the description carries the full disclosure burden. It does add real behavioral context by explaining that matching is by vector similarity rather than literal terms, which tells the agent results may be fuzzy. It says nothing about read-only safety, side effects, result limits, or ranking behavior, so the disclosure 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?

Two short sentences, front-loaded with the core action and followed by the distinguishing mechanism. Nothing is wasted, though the mechanism sentence arguably restates the first clause's intent.

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 7-parameter tool with no output schema and no annotations, the description covers the core mechanic but omits any mention of filtering, scoping, or result-sizing behavior, leaving the agent to rely entirely on the schema. Adequate but with clear gaps around the many optional filters.

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

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

Schema description coverage is 86%, so the schema already documents tags, brief, top_k, source, and tags_mode in detail. The description adds only that query is a semantic (optional) search, which is largely redundant with the schema note. 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 specific operation (semantic search) on a specific resource (memories), and adds the mechanism (vector similarity) that explains what makes it different from a keyword lookup. It does not, however, distinguish this from any sibling tool such as remember/forget, so sibling differentiation is absent.

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 when-to-use or when-not-to-use guidance, and no named alternative among the siblings. The implied usage — retrieve memories by meaning rather than exact wording — is inferable but never stated as a selection criterion.

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 zero annotations the description carries the full burden, and it delivers two concrete behavioral facts: memories are stored at user (cross-project) vs project scope, and duplicates with similarity >0.95 overwrite the existing entry rather than creating a new one. That upsert/dedup semantics is genuinely actionable. It still omits permissions, whether an overwrite is destructive, and what is returned.

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 tight sentences with no filler, and the core action is front-loaded before the storage/dedup qualifiers. It is efficient, though arguably too terse given the complete absence of annotations.

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

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

For a mutation tool with no annotations and no output schema, the description covers storage scope and dedup behavior but is silent on the return value (e.g. an ID), permission requirements, and whether an update replaces prior tags or content. Adequate but leaves real gaps an agent would want filled.

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

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

Schema coverage is 100%, with the schema itself carrying rich parameter detail (Markdown content rules for commands/steps, tag list, scope enum). The description only adds the gloss that "user" means cross-project, which is a marginal clarification over the schema's bare "作用域".

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?

"存入一条记忆" gives a specific verb (store) and resource (a memory), immediately distinguishing it from recall/forget/status siblings. However it never explicitly contrasts itself with auto_save, which is the closest sibling and could plausibly also persist content.

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 what the tool does but gives no when-to-use guidance, no conditions for choosing remember over auto_save, and no prerequisites such as required tags or scope selection. The agent must infer all routing 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?

No annotations provided, but the description discloses both modes, read-only nature of progress, auto-aggregation, and the clear_fields workaround. It doesn't mention return format but covers key 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?

Three efficient sentences, no redundancy. Front-loaded with purpose, then mode conditions, then behavioral notes.

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?

Covers main behaviors comprehensively for a 2-param tool. Missing return details but no output schema exists. The description is sufficient for typical use.

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

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

Schema coverage is 100%, baseline 3. Description adds meaning by explaining update is partial, progress is read-only, and clear_fields solves IDE issues, raising it above baseline.

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 reads or updates session state (verb+resource). It distinguishes from siblings like readme, recall, task by being the sole session state tool.

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 explains when to use each mode (read vs update) and how to clear list fields. It lacks explicit exclusions or alternatives but usage is clear given sibling 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 behavioral-disclosure burden. It usefully discloses that update auto-syncs tasks.md checkboxes across all IDEs and linked issue status, and that archive moves all tasks in a feature group to an archive table. However, it does not describe delete permanence, batch_create failure behavior, list read-only nature, or permission/auth requirements.

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 front-loaded with the tool's scope and action list, then adds only the most important behavioral notes for update and archive. It is concise and well-structured, though it could more clearly separate action-specific usage conditions.

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 six parameters, no annotations, no output schema, and moderate complexity, the description is only partially complete. It covers update and archive side effects but leaves delete, batch_create, and list behavior largely inferred from names and schema, which is insufficient for a mutation tool with no annotation safety profile.

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

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

Schema description coverage is high at 83%, so the schema already documents most parameters including tasks, title, status, task_id, and feature_id. The description adds no parameter-level syntax or format details beyond what the schema provides, making the baseline 3 appropriate.

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

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

The description clearly names the resource (任务) and the available actions (batch_create/update/list/delete/archive), giving a specific verb+resource overview. It does not explicitly differentiate this tool from sibling tools such as track, but the task-management scope is unambiguous enough for an agent to understand its 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?

Usage is implied by the action names and by action-specific notes for update and archive, but there is no explicit guidance on when to use each action versus alternatives, nor when not to use this tool. The schema adds a required-feature_id condition for list, but the description itself does not state 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?

No annotations are provided, so the description carries the full behavioral burden, yet it says nothing about the destructive/reversible nature of archive and delete, required permissions, or side effects. Listing action names conveys what operations exist but not their behavioral consequences.

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 short sentence with no wasted words, and the resource is front-loaded before the action list. It is efficiently sized, though the brevity comes at the cost of 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?

This is a 17-parameter, five-action multi-tool with no annotations and no output schema, so the description should clarify how parameters map to actions and flag destructive operations. Instead it provides only an action list, leaving the agent to reconstruct per-action semantics from the schema alone.

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 88%, so the schema already documents the parameters well (e.g., content for create, brief/limit/issue_id for list). The description adds no parameter meaning beyond the schema, so the baseline of 3 applies.

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 clear resource (issue tracking) and enumerates the five actions the tool performs (create/update/archive/delete/list), so an agent can grasp the tool's scope. It does not differentiate from siblings like task or status, but the verb+resource pairing is specific.

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

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

The description only lists the available actions; it gives no guidance on when to use this tool versus siblings such as task or status, and no conditions or prerequisites for choosing a given action. Usage must be inferred entirely from the bare action names.

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