Cuba-Memorys
Server Quality Checklist
Latest release: v0.21.0
- Disambiguation5/5
Each tool has a clearly distinct purpose, from entity CRUD (cuba_alma) to error tracking (cuba_alarma, cuba_remedio, cuba_expediente) to search (cuba_faro) and maintenance (cuba_zafra). No two tools appear to do the same thing, even within related domains like error handling or memory operations.
Naming Consistency5/5All tools follow a consistent cuba_ prefix and snake_case naming, with single-word or compound names like cuba_pre_compact. The pattern is uniform, making it easy for an agent to predict tool names based on concept.
Tool Count4/5With 28 tools, the count is higher than typical, but each tool serves a specialized function within a complex knowledge graph system. The scope justifies the number, though it might be slightly overwhelming for simple use cases.
Completeness5/5The tool set covers the full lifecycle: CRUD for entities and relations, search, error handling, sessions, decisions, bulk ingestion, sync, audit logs, working memory, hypothesis, contradiction detection, and more. No obvious gaps exist for a comprehensive memory management server.
Average 3.7/5 across 28 of 28 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
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This repository is licensed under Apache 2.0.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
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 mentions 'Relations strengthen with use (Hebbian)' but does not explain what that means for the agent (e.g., automatic persistence, side effects). Critically, the delete action is omitted entirely, leaving a major behavioral gap unaddressed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two sentences) and front-loaded, but it omits the delete action entirely. This conciseness comes at the cost of completeness. Every sentence is functional, but the omission is a critical gap.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 9 parameters, multiple actions, no output schema, and no annotations, the description is moderately complete. It covers create, traverse, infer, and predict, but misses delete and does not explain how bidirectional, persist, or max_depth interact with the overall behavior. The Hebbian mention is vague.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds some context (e.g., Hebbian strengthening and Adamic-Adar for predict), but this largely duplicates what's already in the action parameter description. It does not significantly deepen understanding of individual parameters beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Create edges between entities' but the tool also includes delete, traverse, infer, and predict actions. The first sentence is misleading as it implies only creation. It lists the relation types and explains other actions, but fails to mention delete, making the purpose incomplete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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., cuba_vigia, cuba_proyecto). The description details when to use each action within the tool (traverse vs infer vs predict), but does not help an agent choose between this and other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only offers brief parenthetical hints (e.g., 'stratified exponential by type') but does not explain side effects, required permissions, or irreversible actions like prune or merge.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, using a single sentence with parenthetical clarifications. However, the structure is a flat list, which reduces readability and may omit important contextual details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given 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 is incomplete. It fails to explain return values, error conditions, or how the tool integrates with the broader system, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond the schema; it merely lists actions without detailing how parameters like 'halflife_days' or 'similarity_threshold' affect behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Memory maintenance' and lists actions, providing a general purpose. However, it does not clearly distinguish this tool from similar sibling tools like cuba_forget or cuba_reflexion, and the list format lacks a clear verb+resource structure.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. The description does not mention use cases, prerequisites, or conditions under which specific actions (e.g., decay vs. prune) are appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only says 'record and query' without specifying side effects (e.g., does recording overwrite or append?), persistence, permissions, or any constraints. The agent is left guessing about the tool's effect on system state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the purpose without waste. It is front-loaded and easy to parse. However, given 7 parameters and 3 actions, one sentence may under-communicate, but it is still appropriately concise for a minimal definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description fails to explain what each action returns, how errors are handled, or how parameters interact. For a tool with multiple actions and several parameters, this lack of context leaves the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%—all seven parameters have inline descriptions. The tool description adds no additional meaning beyond what the schema already provides. Baseline 3 is appropriate since the schema fills the semantics gap adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool records and queries architecture/design decisions. It identifies the specific resource type and includes both actions. However, given the 27 sibling tools with similar naming patterns (cuba_*), it does not differentiate itself. A score of 4 reflects clear purpose but no sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 versus siblings or when to choose among its three actions (record, query, list). It does not mention any prerequisites or exclusions. With many similar tools, the lack of usage context is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that 'trust' returns credibility updated by resolve outcomes, but doesn't clarify if other actions modify data, auth requirements, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with front-loaded purpose. However, jargon like 'P(correct|level)' and references reduce accessibility.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema; description lacks details on return formats for actions like 'stats', 'history', and 'resolve'. Incomplete for a multi-action calibration tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all parameters (100% coverage). Description adds minor context for 'trust' and 'metrics' actions with references, but doesn't significantly enhance understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states it performs Bayesian confidence calibration, tracking predictions and computing probabilities. It clearly identifies the resource and verb, but doesn't differentiate from sibling tools like cuba_faro or cuba_eco, which might have overlapping functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description mentions closing a feedback loop but doesn't specify context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that positive/negative affect importance (Oja's rule), correct updates content, and quarantine actions change retrievability. However, it omits side effects like whether changes are reversible, rate limits, or interaction with other tools. Not contradictory but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences pack multiple concepts, but they are front-loaded with the main purpose. No fluff. Could be clearer by separating feedback and quarantine into bullet points, but no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite 100% schema coverage and 5 parameters, the description fails to explain how parameters like entity_name and observation_id relate to each action, or what the tool returns (no output schema). The agent must guess parameter usage for each action, making the description insufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already documented. The description adds context about Oja's rule and quarantine semantics, but does not clarify action-parameter dependencies (e.g., which parameters are needed for each action). Value added is marginal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool handles RLHF feedback (positive/negative/correct) and quarantine gate actions (pending/promote/quarantine), specifying verbs like 'boosts importance', 'decreases', 'updates content', 'lists', 'promote', 'quarantine', and resources (memories/observations). It distinguishes the two main sub-functions, though the jargon 'Oja's rule' may reduce clarity for some agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus its 28 siblings (e.g., cuba_calibrar, cuba_cronica). No prerequisites, success criteria, or examples of when each action is appropriate are provided. The agent must infer from action names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description reveals that the tool returns a warning if a similar approach failed before (via 'proposed_action'), but with no annotations provided, it fails to disclose other behavioral traits such as read-only status, required permissions, or potential side effects. The behavioral transparency is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no unnecessary words. Every sentence adds value—the first states what the tool does, the second gives a key usage hint. Excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is brief and lacks details about return values, result ordering, pagination, or error handling. While the tool has a moderate number of parameters (4), the lack of output schema and limited context means the description is minimally complete for an effective search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full descriptions for all 4 parameters (100% coverage). The description adds a brief usage note about 'proposed_action,' but it does not provide additional meaning beyond what the schema already states. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search past errors/solutions.' It uses a specific verb and resource, making it distinct from vague descriptions. However, it does not explicitly differentiate from siblings like cuba_remedio (which might also deal with errors/solutions), but the purpose is still clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a specific usage tip for the 'proposed_action' parameter, but it lacks any guidance on when to use this tool versus alternative tools (e.g., cuba_remedio or cuba_cronica). No mention of context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses automatic pattern detection (≥3 similar = warning) and Hebbian learning (similar errors boosted). This is useful behavioral context. However, it does not explain side effects like whether entries are created or notifications sent, and no annotations exist to supplement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the core action. No wasted words, but the second sentence could be more structured. Overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description covers the tool's behavior adequately but lacks details on return values, error handling, or prerequisites. It is minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description does not need to add much. It repeats parameter details already in the schema. The extra behavioral info about patterns and boosting relates to tool function, not parameter semantics. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Report errors immediately.' It also mentions auto-detection of patterns and Hebbian learning, which adds specificity. However, it does not explicitly differentiate from sibling tools like cuba_vigia or cuba_centinela.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description only says 'Report errors immediately,' implying when to use, but provides no guidance on when not to use or alternatives among siblings. No explicit context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals that the optional 'project' arg triggers an upsert into brain_projects and scopes subsequent operations, which is helpful. However, it does not describe side effects of 'start' or 'end' actions (e.g., whether sessions are persisted, overwritten, or conflict), leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, with the first clearly stating the tool's purpose and the second explaining the key parameter. It is concise and front-loaded. However, it could be improved by structuring the information (e.g., bullet points for actions) to aid scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters (1 required), no output schema, and no annotations, the description should cover return values, behavior for each action, and edge cases (e.g., what happens if 'end' is called without 'start'). It only elaborates on the 'project' parameter, leaving many scenarios undocumented, making it incomplete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining that the 'project' parameter binds the session to a named project (upserts in brain_projects) and that omitting it keeps the session global. It also contextualizes the 'action' enum by implying start/end/list/current usage, though explicit mapping to each action's behavior is missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool tracks working sessions with goals and outcomes, using a specific verb ('track') and resource ('sessions'). It also mentions the optional project argument for binding. However, it does not distinguish its purpose from sibling tools like cuba_vigia or cuba_proyecto, leaving some ambiguity for the agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks explicit guidance on when to use this tool versus alternatives. It mentions actions (start, end, list, current) but does not specify prerequisites, fallback strategies, or scenarios where other tools would be preferred (e.g., if only logging notes). An agent would need to infer usage from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It mentions version v0.9 and that 'structural' returns specific centralities, but does not disclose whether the tool is read-only, has side effects, requires authorization, or any other behavioral aspects. The description is insufficient for a agent to understand the tool's safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, listing all metrics in a clear, scannable format. Every sentence adds value, and there is no extraneous text. The structure is appropriate for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single enum parameter and no output schema, the description gives a reasonable idea of what each metric returns. However, it lacks details on output format, return structure, or error handling. For a tool with multiple analytic capabilities, an agent might need more context on how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the single parameter 'metric' with detailed enum values, including the v0.9 note. The tool description adds an overview of each metric's output, but this is largely redundant. Since schema coverage is 100%, the description provides minimal additional value beyond a summary.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool performs knowledge graph analytics and lists all specific metrics (summary, health, drift, communities, bridges, structural) with brief explanations. It distinguishes itself from sibling tools which have different purposes (e.g., cuba_proyecto, cuba_alma).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It only lists what metrics are available without context about appropriate use cases or exclusions. No comparison with sibling tools is made.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It discloses read-only nature and method used, but lacks details on return format, error handling, or behavior when no contradictions are found. Partial transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences front-load the purpose and key behavioral trait (read-only). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and description does not explain return values or response format. For a tool involving contradiction detection with embedded methods, the description is insufficient for an agent to fully anticipate results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with adequate parameter descriptions. Tool description adds no extra parameter semantics beyond method context, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'detect' and resource 'semantic contradictions between observations'. It specifies the method (embedding cosine distance + negation heuristics) and explicitly notes it's read-only, distinguishing it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings or when not to use it. The 'read-only' note implies safety but does not provide context for selection among alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains the core behavior (triggers fire on conditions) but omits details on trigger lifecycle, persistence, side effects, and the effect of parameters like max_fires and expires_at. With no annotations, more transparency is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise at two sentences; front-loaded with the key concept. The quote example adds clarity but could be integrated more smoothly. Still, it earns its place and avoids redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has multiple actions (create, list, delete, check) but the description only implies creation. No mention of managing triggers (listing, deleting) or what the output is after creation. Given the complexity and no output schema, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by contextualizing parameters (e.g., 'message' as reminder, 'condition_type' as events). The prospective memory framing ties parameters together meaningfully, exceeding baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: setting triggers for prospective memory, with specific event types (entity access, session start, error match). The example quote reinforces the intent. It distinguishes from sibling tools by focusing on trigger-based reminders tied to specific conditions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for setting reminders conditioned on events, but does not explicitly state when to use this tool versus alternatives like alarms or watches. No exclusions or guidance on when not to use it are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It discloses that all routes share a dedup/PE-gating/embedding pipeline and none delete, and explains the quarantine behavior via the 'untrusted' parameter. This adds meaningful behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear front-loaded purpose and bullet-like explanations for each action. It is moderately concise, though slightly verbose; each sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers actions, parameters, and behavioral aspects adequately, but lacks information about return values or output format. Since no output schema exists, the description could be more complete by describing what each action returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the description adds extra meaning: it explains each action mode, the quarantine behavior of 'untrusted', and the knowledge-update feature of 'supersede_conflicts'. This provides value beyond the parameter descriptions in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Bulk knowledge ingestion' and lists three specific actions (ingest, parse, auto_extract) with brief explanations. It distinguishes the tool's function but does not explicitly differentiate from sibling tools like cuba_faro or cuba_eco.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context for when to use each action (e.g., 'ingest for structured items', 'parse for raw text splitting'), but lacks explicit guidance on when not to use this tool or mentions of alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses memory isolation and session binding but does not explain behavioral traits for actions like rename or merge (e.g., whether they are destructive, require permissions). The description is partially transparent but leaves gaps for a tool with multiple actions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences cover the core concept efficiently. The inclusion of 'v0.8' is minor clutter. Front-loaded with essential information. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 3 parameters, the description is reasonably complete. It explains the isolation mechanism, session binding, and legacy behavior. However, it lacks details on return values or effects of each action, which could be inferred but are not explicit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context about project scoping and session binding but does not elaborate on parameter semantics beyond what the schema provides. Adequate but not enhanced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: project scoping to isolate memories per project. It uses a specific verb ('isolate') and resource ('memories per project'), and distinguishes it from sibling tools by focusing on project management concepts like session binding and legacy rows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that the active project is bound to the session via cuba_jornada start --project NAME, and notes legacy row visibility. However, it does not provide explicit when-to-use or when-not-to-use guidance relative to sibling tools like cuba_jornada or cuba_alma. The usage context is implied but not clearly delineated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and mentions key behaviors: auto-creating entities, dedup gate for near-duplicates, and supporting episodic memory actions. It could add more details on side effects or error handling but is above average.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph of three sentences, concise and front-loaded. However, it is dense and could benefit from breaking into bullet points for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters, multiple actions, no output schema, no annotations, the description covers core functionalities but lacks details on return values, error conditions, and action-specific constraints. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context for action values (e.g., 'episode_add stores a temporal event') but does not significantly enhance parameter meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool attaches facts/lessons/decisions to entities and manages episodic memories with actions like episode_add, episode_list, and timeline. It distinguishes itself from siblings by specifying unique functionalities such as auto-creating entities and dedup gates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for attaching observations and managing memories but lacks explicit guidance on when not to use or alternatives among the 27 sibling tools. No 'when-to-use' or 'when-not-to-use' advice is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden and explicitly states 'Read-only introspection', confirming no destructive actions. It also details the specific gap types analyzed, providing good transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no redundancy. Every sentence adds value and is efficiently worded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input schema and no output schema, the description adequately explains the tool's function and scope. However, the lack of any mention of output format or return value is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'action' with enum 'analyze' is fully covered by the schema (100% coverage). The description adds the list of gap types, but it's not directly about parameter syntax or options, so baseline score is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes knowledge graph for structural gaps, listing specific gap types. However, it does not differentiate from sibling tools, which lowers the score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for finding structural gaps but lacks explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavior. It mentions cross-referencing but does not detail side effects like status changes, permissions, or irreversibility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, concise and front-loaded. However, the cross-referencing note is vague and could be clearer.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers the main action but lacks details on what 'mark as resolved' entails (e.g., state change) and what 'cross-references' produces.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The tool description adds no additional parameter-specific semantics beyond cross-referencing, which is a behavioral note.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: marking an error as resolved with a solution. It also mentions cross-referencing similar unresolved errors, which distinguishes it from sibling tools like cuba_vigia or cuba_alarma.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for resolving errors and cross-referencing similar ones, but does not explicitly state when not to use it or provide alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It explains the learning mechanism (recording outcomes), the ranking by reliability, and that re-adding a name edits it while keeping its track record. This gives agents good insight into the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat verbose and metaphorical ('PROCEDURAL MEMORY', 'the other tools remember what is TRUE'). While it is front-loaded and clear, it could be more concise by reducing philosophical framing. Every sentence adds some value, but some could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, 1 required, no output schema), the description provides enough context to use it correctly. It explains the core mechanics and the outcome reporting. However, it could be more explicit about parameter relationships and usage patterns beyond actions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant meaning beyond the schema. It explains the purpose of each action (e.g., 'outcome: record success/failure — this is what teaches it') and the concept of procedural memory. This helps an agent understand how to use the parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a procedural memory for how things are done, distinguishing it from sibling tools that remember facts. It specifies actions like bringing up dev services, running tests, deploying, migrating. However, the metaphorical language ('PROCEDURAL MEMORY', 'the other tools remember what is TRUE') slightly obscures the direct function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on reporting outcomes using the 'outcome' action for learning, and warns that failing recipes are harmful. It implies usage context but does not explicitly state when not to use this tool or list alternative tools for specific scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosure. It reveals key behaviors: export writes one JSON file per entity, import uses INSERT ON CONFLICT DO NOTHING (idempotent), diff compares disk vs DB, and status lists manifests. It also clarifies that embeddings are omitted by default. This is fairly transparent, though it could mention potential side effects like directory creation or permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph that efficiently conveys the core information (purpose, actions, defaults). It is front-loaded with the main purpose. However, it could be improved with bullet points or separate sentences for each action to enhance scanability. Every sentence adds value, but the structure could be cleaner.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no annotations, and no output schema, the description covers the essential aspects: all four actions, default directory, conflict handling for import, and embedding behavior. It lacks details on return values or error handling, but the actions (diff, status) imply comparisons and listings. The description is sufficient for typical usage scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds meaningful context beyond the schema: it explains the default directory derivation, the idempotent nature of import, and that embeddings are excluded by default. This enhances understanding of the 'dir', 'action', 'conflict', and 'with_embeddings' parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Git-friendly export/import of the knowledge graph (v0.8).' It enumerates four distinct actions (export, import, diff, status) with brief explanations, making it easy to distinguish from sibling tools like cuba_vigia or cuba_proyecto which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description fails to provide guidance on when to use this tool versus alternatives. It explains what each action does but does not specify contexts or trade-offs (e.g., when to use 'import' with 'merge' vs 'overwrite', or when 'diff' is appropriate). No explicit 'when-to-use' or 'when-not-to-use' statements are present.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that behavior is identical to direct calls via the same dispatcher, which is helpful. However, it does not mention potential side effects, error handling for unknown tools, or permission requirements, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences), front-loaded with the core purpose, and each sentence adds value—first defines the action, second gives usage guidance and behavioral note. No extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity as a generic caller and lack of output schema, the description is fairly complete. It explains how to discover other tools and confirms identical behavior. Missing details like error messages or argument handling corner cases, but these are minor for the task.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both 'tool' and 'args'. The description adds value by explaining that args must match the invoked tool's schema, but this is largely redundant with the schema descriptions. No additional semantic details are provided beyond what the schema already conveys.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool invokes any cuba-memorys tool by name, including those not pre-loaded, distinguishing it from the sibling tools which are specific functions. The verb 'invoke' and resource 'any tool' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises discovering tools first with cuba_tools using detail='full', providing clear context for dynamic invocation. It implicitly differentiates from direct calls by noting tools may not be pre-loaded, though it doesn't explicitly state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully covers behavioral traits: it states the operation is 'cascading', 'hard-delete', 'IRREVERSIBLE', and lists affected areas (observations, relations, errors, sessions). No contradictions found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero filler. First sentence states the action and scope; second sentence emphasizes irreversibility and a precondition. Every word is purposeful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no output schema, the description provides ample context about the effect and prerequisites. It could mention the return value (e.g., success/error), but the warnings make it largely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for both parameters. The description adds the safety requirement 'Requires confirm=true' but does not significantly enhance understanding beyond schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('cascading hard-delete') and clearly identifies the resource ('entity and ALL references across observations, relations, errors, and sessions'). It distinguishes itself from sibling tools like 'cuba_receta' or 'cuba_archivo' by focusing on complete erasure.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'GDPR Right to Erasure' as a use case and highlights the need for 'confirm=true', but does not explicitly state when not to use it or compare it to alternatives among siblings. Clear context but lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It describes the actions' effects (persisting and retrieving a summary), but lacks detail on error handling, what happens if called at other times, or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, efficiently front-loading the protocol name and version, then clearly specifying the two actions and their timing. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a single parameter, the description is fairly complete. It tells the agent exactly when to call each action, though it omits potential edge cases or failure modes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter with 100% description coverage. The description adds value by embedding the protocol context (snapshot before compact, restore after), which goes beyond the schema's simple enum description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's purpose: providing snapshot and restore actions for session state during compaction. It clearly distinguishes itself from sibling tools, none of which serve this specific protocol.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit when to use each action: call action='snapshot' before /compact and action='restore' after. This provides clear context, though it does not mention alternative tools 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.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full behavioral burden. It goes beyond CRUD by stating 'Auto-boosts neighbors on access,' which is a notable behavioral trait. However, it does not detail what happens on delete or any authorization needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states purpose and resource, second adds behavioral trait and sibling alternative. Every sentence earns its place, with no wasted words. Front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description could mention what the tool returns (e.g., the entity object). However, for a CRUD tool with clear input schema, the description is largely complete for invocation. The auto-boost behavior is a nice addition.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context that entity_type can be one of the listed types, but for most properties, the schema's descriptions are already sufficient. The description does not add significant new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'CRUD knowledge graph entities (concepts, projects, technologies, patterns, people)', which specifies the verb (CRUD) and resource (knowledge graph entities). It distinguishes itself from sibling cuba_cronica by noting that tool is for transient info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides a usage guideline: 'For transient info use cuba_cronica instead.' This tells the agent when not to use this tool and what alternative to choose, which is strong guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fully discloses core behaviors: append-only, SHA-256 hash chain, UPDATE/DELETE blocked at trigger level with admin bypass. No annotations were provided, so the description carries the full burden. It does not mention rate limits or payload size limits, but the behavioral details are substantial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, followed by technical details and usage guidance. No extraneous content. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's main purpose, security model, and available operations. Given no output schema, it could mention return values (e.g., verify returns chain results, tail returns events, append returns success). However, the provided details are sufficient for an audit log tool with moderate complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing descriptions for all four parameters. The description adds value by specifying default limits for 'verify/tail' and clarifying that payload and event_action are for 'append'. This goes beyond the schema's attribute descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly identifies the tool as a 'Tamper-evident audit log' with specific operations (append, verify, tail) and technical details (SHA-256 hash chain, append-only). This clearly defines the resource and verb, and the unique hash chain feature distinguishes it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use each action ('Use 'verify' to walk the chain...'tail' to read recent events...'append' to add a new event'). However, it does not discuss when not to use the tool or alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description adequately discloses behavioral traits: it is a search (read-only) operation, returns grounding scores, supports temporal filtering, and details version-specific features. It does not mention authentication or rate limits, but these are less critical for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at 4-5 sentences, front-loaded with the primary purpose, and efficiently lists key features and version numbers without extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 16 parameters and no output schema, the description covers the essential behavior, including temporal filtering, modes, and versioned features. It could briefly mention the return structure (e.g., list of results) but overall is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant value beyond the 100% schema coverage by explaining parameter contexts (e.g., '71% fewer tokens' for format, 'cross-encoder rerank' for rerank, defaults and version details). This enriches understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's core function: 'Search memory BEFORE answering to ground responses.' It specifies modes ('verify') with confidence levels, session-aware boosting, and temporal filtering, distinguishing it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for use (grounding responses) and explains the primary modes. However, it lacks explicit guidance on when not to use this tool versus siblings, which would be helpful given the large sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description fully carries the burden. It discloses the LLM call via subprocess (Claude Code CLI or Anthropic API), cost implications ($0 with subscription), caching (UNIQUE per pair = permanent), and cost control via max_pairs. This is thorough behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each earning its place: purpose, context, mechanism, caching. Front-loaded with the core purpose and progressively adds detail. No filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers parameters and behavior well, but the absence of an output schema means the description should clarify what the tool returns (e.g., verdict, status). It mentions verdict persistence but not the immediate response. This leaves ambiguity for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the two action modes (judge_pair vs scan_entity), default max_pairs (5), and cost control implications. However, it does not add extra meaning for observation_a/b or entity_name beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is an 'LLM-judge for semantically-conflicting observations' with a specific trigger condition (cosine similarity 0.6-0.8). It defines its scope and differentiates from heuristic detectors, making its unique role apparent even among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context: when cosine similarity sits in the ambiguous band and heuristic detectors fail. However, it does not explicitly state when not to use the tool or mention alternative tools for other scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key behaviors: TTL-bound, auto-expire, bulk-purge by another tool, and the three operations (write, read, clear). Does not explicitly state if write overwrites or appends, but given the scratchpad semantics, it's implied. Overall, informative for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the model name and purpose. Every clause is informative and contributes to understanding. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description covers purpose, usage, parameter behavior, and lifecycle (expiry and purge). It also references a related sibling tool (cuba_zafra) for additional context, making it self-contained and complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining tag filtering for read/clear, default TTL, and the action enum implicitly. The context 'Content to store (for write)' clarifies optional fields. This exceeds the schema's minimal descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly defines as a working memory buffer, references the Baddeley 1992 model, and distinguishes itself from episodic and semantic memory. Lists specific use cases (inter-step plan state, tentative observations, cross-tool-call reminders) and differentiates from sibling tools like cuba_cronica (episodic) and cuba_alma (semantic).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to use for inter-step plan state during long-horizon tasks, tentative observations, and reminders. Mentions auto-expire by ttl_seconds and bulk-purge by cuba_zafra REM cycle, providing context on lifecycle. Lacks explicit 'when not to use' but the positive guidance is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the on-demand loading behavior, profile sensitivity, and that this tool is for discovery only. It does not mention side effects, but for a read-only discovery tool, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundancy. Front-loaded with main purpose, then provides details on usage and parameters. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains what each detail level returns. It mentions the total tool count, the lean profile context, and the workflow (search then call with cuba_call). It is complete for a discovery tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds significant value: explains detail level trade-offs ('cheapest'), what each detail returns, and that 'full' gives the schema needed to call the tool. This goes beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds cuba-memorys tools and loads their schemas on demand. It specifies the verb 'find' and resource 'tools + schemas', and distinguishes from siblings by explaining its role in lazy loading and discovery, contrasting with execution tools like cuba_call.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: when tools are not pre-loaded under the lean profile. It recommends searching by capability and gives examples. It does not explicitly list scenarios to avoid, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full burden. It explicitly states 'Read-only', describes the ranking formula (path_strength × importance), and mentions traversing causal relations backwards. This fully discloses the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose. Every word adds value, no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an inference tool with 4 parameters and no output schema, the description is complete. It explains what the tool does, how results are ranked, and that it is read-only. No missing information critically needed for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant context: explaining abductive inference, the ranking method, and the read-only nature. This enhances understanding of each parameter's role beyond their individual descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies 'abductive inference' with a clear verb+resource: given an observed effect, find plausible causes by traversing causal relations backwards. It distinguishes from siblings by focusing on hypothesis generation. No other sibling tool suggests this abductive role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states when to use: when you have an observed effect and need plausible causes. It does not explicitly state when not to use or mention alternatives, but the context is clear enough for an agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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