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-style query and the synthesizing behavior. It does not mention potential side effects or limitations, but for this tool's simple query nature, the description is adequate.

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 no filler. The RAG analogy clarifies the behavior without adding length.

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

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

A simple tool with one parameter and no output schema. The description fully conveys purpose, input scope, and output nature, making it complete for its 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?

Schema description coverage is 100% for the single parameter 'question', and the description adds no extra meaning beyond what the schema already provides. 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 clearly states a specific action: asking a question and receiving a synthesized answer from project memories. It distinguishes itself from sibling tools by emphasizing synthesis rather than raw recall or search.

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 usage context is implied: use when you want a synthesized answer over project knowledge. However, it does not explicitly contrast with siblings like memory_recall or memory_search, which are likely alternatives for direct retrieval.

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 must disclose side effects. It says 'gets written to CLAUDE.md', implying a file write, but does not mention whether it overwrites existing content, requires prior memory state, or changes anything else. This is a significant transparency gap for a potentially mutating 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?

Two short sentences, front-loaded with the main action and a clarifying detail. No wasted words, and the connection to CLAUDE.md adds value without verbose explanation.

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 zero-parameter tool in terms of basic function, but it lacks guidance on when to run it, what happens to existing CLAUDE.md content, and how this relates to the memory lifecycle (init, save, consolidate). Without annotations or an output schema, it should provide at least a note about side effects.

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 0 parameters, so the schema provides no parameter descriptions. The baseline for tools with no params is 4, and the description adds relevant context about the output destination ('written to CLAUDE.md'), which is useful for understanding the tool's behavior.

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 'Generate' and names the resource 'the full consciousness document', then ties it to a concrete output location ('written to CLAUDE.md'). This clearly distinguishes it from the sibling memory tools, which focus on saving/recalling/searching memory items rather than producing the overall consciousness document.

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 on when to use this tool versus alternatives. The only contextual hint is that it generates the consciousness document that gets written to CLAUDE.md, but it doesn't state prerequisites, ordering, or situations where this is preferred over memory_init or memory_consolidate.

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 does disclose that the tool merges duplicates and removes outdated memories, which implies a destructive action. However, it does not warn about permanence, reversibility, or potential data loss, leaving some ambiguity about the 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?

The description is a single, focused sentence that front-loads the primary verb and resource, followed by clarifying actions. There is no fluff or repetition, making it extremely concise and well-structured.

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

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

The tool is simple (0 parameters, no output schema), and the description explains what it does. However, it omits what the agent should expect after triggering (e.g., no return value description, no confirmation behavior). Given the lack of annotations and output schema, this is a noticeable gap but not fatal.

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 100% (trivially). The description does not need to explain parameters, and the baseline for 0-parameter tools is 4. It appropriately adds no redundant parameter information.

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 with a specific verb ('trigger') and resource ('memory consolidation'). It further elaborates with concrete actions (merges duplicates, removes outdated memories), which distinguishes it from sibling tools like memory_save or memory_delete.

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 'Manually trigger' implies that the tool is for on-demand maintenance, but it does not provide explicit guidance on when to use it versus alternatives. No mention of prerequisites or typical use cases, so the usage is only implied, not clearly instructed.

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 bears the full burden of disclosing behavioral traits. It indicates a destructive action ('Delete') but does not mention irreversibility, confirmation requirements, cascading effects, or result feedback. The description adds no extra disclosure beyond the obvious mutation.

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, direct sentence with no fluff. Every word earns its place, and the key information (action and target) is front-loaded.

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 simplicity (one parameter, straightforward delete operation) and the high schema coverage, the description is sufficiently complete for basic invocation. It lacks behavioral transparency details (e.g., results) but remains adequate for a simple deletion 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 input schema already covers the sole parameter 'id' with a clear description ('Memory ID to delete'), so schema coverage is 100%. The description does not add any further semantic detail beyond what the schema provides, hence the baseline score of 3.

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 ('Delete') and resource ('memory by ID'), clearly distinguishing it from sibling tools like memory_save or memory_search. It is concise and 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 alternatives, no mention of prerequisites, exclusions, or scenarios where deletion is appropriate or inappropriate. The description simply states the action without contextual usage cues.

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 must disclose behavioral traits. It does not mention side effects, idempotency, whether it overwrites existing memory, or any prerequisites. For a mutation tool like this, the lack of such transparency is a significant gap.

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 exactly one sentence, front-loaded with the primary action, and contains no unnecessary words. It is highly concise and 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?

The tool is simple with only two parameters fully described in the schema, making the description minimally adequate. However, with no output schema and no annotations, the description does not explain return values, idempotency, or the consequences of initialization, leaving it incomplete for a mutation tool.

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

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

Schema coverage is 100% with clear descriptions for both parameters ('Project name' and 'Brief project description'). The description merely repeats the parameter names without adding additional meaning, so it stays at the baseline of 3.

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 the specific verb 'Initialize' with the resource 'project memory' and mentions the key inputs (name and description). This clearly distinguishes it from sibling tools like memory_save or memory_recall, which operate on existing memory.

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 verb 'Initialize' implies that this tool is for setting up new project memory, which suggests when to use it, but the description does not explicitly state when to use it versus alternatives or mention any exclusions. This is implied usage rather than clear 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?

No annotations are provided, so the description carries the full burden. It does not define what 'active' means, nor does it mention pagination, ordering, or limits. While 'recall' clearly implies a read operation, the meaning of 'active' is a significant ambiguity.

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

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

The description is a single, well-structured sentence that leads with the verb and resource. It contains no fluff and communicates the core functionality 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 simple filtered-list tool, the description is adequate, but it leaves key context unexplained: the meaning of 'active' and the expected return format (since no output schema exists). The lack of such details reduces 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 input schema already provides 100% coverage, including detailed enum descriptions for the 'type' parameter. The description simply echoes 'filtered by type or tags' without adding any new meaning or context 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 recalls all active memories with optional filtering by type or tags. It uses a specific verb and resource, and the phrase 'all active' distinguishes it from siblings like memory_search or memory_related.

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 clearly implies the primary use case: retrieving the complete set of active memories, with the option to narrow results. It does not explicitly mention alternatives or exclusions, but the context of filtering is clear.

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

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

No annotations are provided, so the description must fully disclose behavior. It only says 'Get all memories related to specific tags/areas,' without clarifying ordering, result limits, matching semantics, or output shape. The vague 'related to' leaves significant behavioral uncertainty.

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 the action front-loaded. Every word earners its place; there is no filler 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 tool is simple and the schema is rich with parameter descriptions. However, there is no output schema, no mention of result shape or behavior, and no differentiation from memory_search, so the description is adequate but leaves gaps.

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

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

Schema coverage is 100%, and the enum descriptions fully explain the 'type' parameter. The description adds minimal meaning beyond the schema, so 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 clearly states a specific action and resource: 'Get all memories related to specific tags/areas.' This distinguishes it from obvious write/delete siblings, but it does not explicitly contrast with similar lookup tools like memory_search or memory_recall, leaving some 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 explicitly says 'Use to explore a topic in depth,' giving a clear context for when this tool is appropriate. It does not mention exclusions or alternatives, but this is acceptable for a straightforward read tool among siblings.

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 carry the behavioral burden. It states the core behavior 'Save a memory' and lists content types, but it does not disclose side effects, whether it appends or replaces (despite the 'supersedes' parameter), or any requirements like prior initialization. This meets a minimal threshold but leaves significant gaps.

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

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

The description is two sentences, front-loaded with the action 'Save a memory about this project', and the second sentence adds useful enumeration of memory types without redundancy or filler.

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 save tool with four parameters and no output schema, the description provides the core purpose and content categories, while the schema handles parameter details. However, it omits mention of prerequisites (e.g., memory_init), return values, and behavior of the 'supersedes' parameter, leaving the description moderately 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 input schema provides 100% coverage with descriptions for all four parameters, so the description adds little beyond the schema. It repeats the type enum values but does not clarify tags, content, or supersedes beyond what the schema already details. 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 clearly states the action 'Save a memory about this project' and enumerates specific content types (decisions, patterns, architecture, gotchas, progress, context). This distinguishes it from sibling tools like memory_recall or memory_delete by establishing a unique 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?

The description implies usage for recording new information for future sessions, but it does not explicitly contrast with alternatives like memory_recall or memory_search. It provides clear context ('about this project') but lacks explicit exclusions or prerequisites, though the action verb 'save' strongly signals when it applies.

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 adds some behavioral detail: results are ranked and search spans content and tags. It implies a read-only operation but does not explicitly state that it does not modify memories, nor does it mention default limits or pagination. With no annotations provided, the description carries the burden and only partially fulfills 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 two sentences long, front-loaded with the verb 'Search', and includes key details without fluff. 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?

As a simple search tool with two parameters and no output schema, the description is mostly adequate. However, it lacks guidance on output format or behavior when no results are found, and the lack of comparison to siblings makes the overall context 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?

The input schema provides 100% coverage for both parameters, with clear descriptions for 'query' and 'limit'. The description does not add any extra meaning beyond the schema, so the baseline score 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 clearly states the tool searches memories by keyword and returns ranked results across content and tags. It is specific and action-oriented, but it does not differentiate itself from sibling tools like memory_recall or memory_related, so it loses a point.

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 on when to use this tool versus alternatives. There is no mention of memory_recall or memory_related, nor any exclusion criteria. The agent must infer usage from the name and description alone.

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

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

With no annotations provided, the description carries the full burden. It indicates a read-only operation through the verb 'Show', but does not explicitly state 'does not modify memory' or describe any side effects. It also does not mention output format or potential costs, leaving some behavioral aspects unspecified.

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, front-loaded with the primary action ('Show memory statistics') and succinctly lists the key details. Every word earns its place; no filler 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 zero-parameter tool with no output schema, the description is sufficiently complete. It states exactly what statistics are shown. However, it does not describe the output structure (e.g., JSON format), which could be useful but is not critical for a simple stats 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 tool accepts zero parameters, so the input schema is empty and the baseline is 4. The description adds no parameter details because there are none; it appropriately focuses on the output content.

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 'Show' with a clear resource 'memory statistics' and enumerates exactly what the stats include (counts by type, active/archived/superseded, last consolidation). This clearly distinguishes it from sibling tools like memory_save or memory_delete.

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 (when memory statistics are needed), but does not explicitly state usage context or exclude alternatives. Sibling tools like memory_consolidate might relate, but the description offers no explicit comparison or when-not-to-use guidance.

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