chimeralang-mcp

by fernandogarzaaa

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.8.1
Disambiguation4/5
Each tool has a specific purpose with detailed descriptions, making them largely distinguishable. However, the high number of tools and some overlapping concepts (e.g., multiple compression-related tools) could cause minor confusion for an agent.
Naming Consistency5/5
All tools follow a consistent 'chimera_' prefix with snake_case names that clearly indicate their function, creating a predictable and uniform naming convention.
Tool Count2/5
With 51 tools, the server is excessively large for typical MCP use cases. This imposes significant token overhead and cognitive load, suggesting the tool set is overengineered and could benefit from consolidation.
Completeness4/5
The tool set covers a wide range of functionalities including cost management, compression, verification, auditing, and caching. Minor gaps exist (e.g., no explicit error handling tool), but the surface is largely comprehensive for its intended domain.
Average 3.5/5 across 51 of 51 tools scored. Lowest: 1.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose any behavioral traits (e.g., side effects of add_edge, read-only for query). The agent has no information about permissions, persistence, or safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences), but it sacrifices essential information. Conciseness under 3 is detrimental because the tool has 9 parameters and multiple actions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 parameters, no output schema, no annotations), the description is critically incomplete. It does not explain return values, parameter relationships, or any constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description adds no meaning for parameters like cause, effect, strength, or source. The agent cannot infer how to use the parameters without additional documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Causal graph' and lists actions (add_edge, query, paths, info), indicating the tool operates on a causal graph. It distinguishes from sibling tools by domain (causal vs. audit, batch, etc.), but lacks detail on what each action does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The long sibling list suggests many tools, but no comparative context is given.
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 must disclose behavioral traits, but it only states actions generically. It does not mention side effects (e.g., whether 'add' overwrites or appends), idempotency, authorization needs, or error behaviors. The term 'keyword-search' hints at search behavior but is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences) and front-loaded, but it sacrifices essential detail for brevity. It is not overly verbose, but extreme conciseness here results in incompleteness. A minimally viable description should at least map parameters to actions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, 3 actions, no output schema), the description is far from complete. It omits return values, error handling, and usage patterns. The information provided is too sparse for an agent to use the tool reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning no parameter descriptions in the schema. The description does not explain any of the six parameters (action, content, category, tags, query, namespace). It lists actions but does not map parameters to actions, leaving the agent unable to construct correct invocations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'keyword-search knowledge base' and lists the actions (add, search, list), giving a specific verb+resource. However, it does not differentiate from the many sibling chimera tools, such as chimera_memory or chimera_claims, which could have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description only lists actions without explaining contexts, prerequisites, or comparisons to sibling tools. An agent would have no basis for choosing chimera_knowledge over other knowledge-related 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 must disclose behavioral traits. It mentions importance scoring but does not explain its effect on storage or recall, nor does it describe side effects, persistence, or concurrency behavior. The actions 'store' and 'recall' are listed without detail on how they modify state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (two sentences) and front-loaded with key concepts. However, it sacrifices clarity and completeness for brevity, which may hinder tool selection.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, no annotations, no output schema), the description is severely incomplete. It fails to explain how to use the parameters, expected return values, or behavior in edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It only lists the 'action' parameter via the two actions but does not explain parameters like content, tags, query, limit, or namespace. Importance is mentioned but not connected to the schema parameter. The description adds minimal meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a session memory store with two actions (store, recall) and mentions importance scoring. However, it does not differentiate from sibling tools like chimera_knowledge or chimera_self_model, which may also involve memory storage and retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context for appropriate usage scenarios, exclusions, or comparisons with other chimera 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?
No annotations provided, so description must disclose behavior. It mentions mapping and actions, but does not indicate whether add_mapping mutates state, requires permissions, or has side effects. Lack of behavioral details limits safe usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very short and front-loaded with the core purpose, but the description omits essential details. While concise, it sacrifices informativeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain return values, required permissions, or how to construct valid analogies.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% parameter description coverage. The description only tangentially references source_domain, target_domain, and concept/analogy, but does not explain the purpose or constraints of any parameter, including confidence, which is ambiguous without context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool maps concepts between domains and lists three actions. It distinguishes itself from sibling tools like chimera_translate or chimera_knowledge by focusing on domain analogy mapping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. Does not explain under what circumstances to use each action (add_mapping, query, list) or when to use this tool over other chimera 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?
No annotations are provided, so the description must disclose all behavioral traits. It only mentions 'confidence-weighted' but does not specify permissions, side effects (e.g., persistence, atomicity), or behavior on invalid keys. This is insufficient for a stateful tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence), which is efficient but lacks necessary detail. It front-loads the key action types but omits structure like parameter explanations or context. It is not overly verbose but sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no output schema, and no annotations, the description should be more complete. It does not explain return values, error conditions, or usage patterns, leaving an agent with insufficient information to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no parameter-level meaning. The terms 'update' and 'query' are mentioned but not linked to the action parameter, and key, value, confidence, namespace are undefined. The schema provides types and defaults, but the description fails to clarify their semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it is a 'confid ence-weighted key-value world state' and lists two actions ('update, query'), giving a clear verb+resource. However, it does not differentiate from sibling tools like chimera_memory or chimera_self_model, which might also involve state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. There is no mention of prerequisites, limitations, or context such as whether updates are reversible or if queries are fast. The description is purely functional.
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 carries the full burden of behavioral transparency. It mentions the tool records adaptation events and lists actions, but fails to disclose side effects (e.g., whether 'record' mutates state, whether 'stats' is read-only), performance implications, or required permissions. This is a significant gap for a tool with write potential.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at two sentences with no redundant words. It is front-loaded with the core purpose. However, the first sentence could be clearer by separating the list 'context, action, outcome' from the enumeration of actions, but it remains terse and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 6 parameters, no output schema, and no annotations, the description is incomplete. It explains the 'action' parameter but leaves the other five parameters unexplained. The behavior of the 'stats' action is not described, and return values are omitted. The tool's overall function is hinted but not fully detailed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning no parameters are explained in the schema. The description adds meaning only for the 'action' parameter by listing valid values 'record' and 'stats'. Other parameters like context, action_taken, outcome, confidence, and namespace are not mentioned at all. Given low coverage, the description should compensate by explaining all parameters but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Record adaptation events (context, action, outcome)' and specifies two actions 'record' and 'stats', giving a specific verb and resource. It distinguishes the tool's function somewhat, but could be clearer on what constitutes an adaptation event and how its two actions differ. Among 50+ sibling tools, it does not strongly differentiate from similar ones like chimera_metacognize.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 is provided. The description only states what the tool does, with no mention of context, prerequisites, or when to choose 'record' vs 'stats'. The large sibling list offers no hints for selection.
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 exist, so description must disclose behavioral traits. It indicates read-only inspection but does not mention idempotency, side effects, auth requirements, or rate limits. Missing crucial context for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with inline list is efficient and front-loaded. No redundancy, matches tool scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite few parameters and no output schema, description omits param interactions (e.g., envelope_id ignored unless action=get), return format, and meaning of 'material pack and security metadata'. Incomplete for confident use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 50% of parameters with descriptions; description adds no extra param details beyond mentioning actions. Missing compensation for undocumented parameters (action command values, namespace role).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description specifies verb 'inspect' and resource 'persisted result envelopes', and lists actions. It clearly distinguishes from sibling tools that do not mention envelopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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. Does not state prerequisites or exclusions. The list of actions provides implied usage but no explicit when/why.
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 exist, and the description does not disclose side effects, permissions, or whether the tool is read-only. It only lists outputs, leaving behavioral traits ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the purpose efficiently. No wasted words, but could benefit from additional structure or clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists outputs but lacks context on the audit scope, format, or when to use it relative to many siblings. It is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no value beyond the schema for the single parameter. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs a session constraint audit and lists the returned metrics. However, it does not explicitly differentiate from similar sibling tools like chimera_session_report, though the focus on constraints provides some distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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, nor any prerequisites or exclusions. The description only states what it does, not when or why to use it.
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. It mentions returning status and recommendation but does not disclose side effects, required permissions, or whether it modifies state. Insufficient for a safe interaction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence that front-loads the core purpose. No wasted words; every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite 100% schema coverage, the description lacks details on how token usage is calculated, threshold criteria for statuses, and implicit behavior. Incomplete for a tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does 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 no additional meaning beyond the schema; each parameter's role is already documented in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares token usage against the context window and returns status and recommendation. However, it does not explicitly distinguish from sibling tools like chimera_compress or chimera_fracture, though the core purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 or prerequisites. The description does not provide context for selection among siblings.
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 provided, and the description does not disclose whether the tool is read-only or has side effects. The summary nature suggests read-only, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with a single sentence that front-loads the purpose. However, it could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description lists expected output fields. Still, it does not explicitly state the output format or any additional context about the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single optional parameter. The description adds no additional meaning beyond the schema's 'Optional persistence namespace'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides a session cost summary with specific metrics (tokens saved, dollars saved, avg compression %, last 10 events). However, it does not distinguish from sibling tools like chimera_cost_estimate or chimera_cost_track.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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. No context on prerequisites 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions decomposing and returning a task list, but does not clarify side effects, permissions, or what 'detects goal type' entails. Missing details on whether it is read-only or mutates state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two sentences), front-loads the primary action, and contains no redundant information. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description should elaborate on return values. It only vaguely mentions 'task list with strategy' without specifying structure, ordering criteria, or what the strategy entails. Incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes the 'goal' parameter. The description adds output behavior but not parameter meaning. Baseline 3 applies as per guidelines.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: decompose a goal into ordered sub-goals, with detection of goal type and return of a task list. It is specific to breaking down goals, which distinguishes it from sibling tools like chimera_deliberate or chimera_explore, though it does not explicitly differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks any conditional context, prerequisites, or indications of when this tool is preferred over similar sibling 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?
No annotations are provided, so the description must disclose behavioral traits. It states 'apply' policies but does not explain what 'apply' entails—e.g., whether it modifies state, requires permissions, or has side effects. This lack of transparency for a mutation-like action 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose and provides concrete examples. It is front-loaded with the verb 'List, inspect, or apply' and the resource 'reusable constraint policies'. The list of policy names adds value without excessive length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not explain return values, the effect of 'apply', or when each action is appropriate. A user or AI agent would need additional documentation to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds context by naming example policies and clarifying the 'inspect' action (mapped to 'get' in the schema). However, it does not explain the 'value', 'envelope', 'tool_name', or 'namespace' parameters. With schema coverage at 50%, the description partially compensates but leaves key parameters unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List, inspect, or apply reusable constraint policies' and provides concrete examples like 'strict_factual, brainstorm, medical_cautious', making the tool's purpose specific. However, it does not explicitly differentiate from sibling tools like chimera_constrain or chimera_gate, so it loses a point for 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists possible actions but gives no guidance on when to use this tool versus alternatives. For instance, there is no mention of prerequisites or scenarios where list vs apply is appropriate, nor any comparison to other chimera tools that might handle similar tasks.
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 disclose behavior. It states the tool records and returns capabilities, but does not clarify side effects, persistence, permissions, or whether updates are reversible. Essential behavioral traits are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences) and front-loads the key concept ('Capability tracker'). It is efficient, but could include a bit more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 undocumented parameters, no output schema, and no annotations, the description leaves significant gaps. The agent lacks critical information about parameters like 'level' and 'namespace', and the return format of 'reflect' is not specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description adds no explanation for the 5 parameters (action, capability, level, evidence, namespace). Only the actions are named; the agent must guess parameter roles from context, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a 'Capability tracker' with two distinct actions: update (record capability+evidence) and reflect (return all capabilities). The verb-resource pairing is specific, but it does not differentiate from sibling tools like chimera_knowledge or chimera_claims that might also track capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use each action (update to record, reflect to retrieve), but lacks guidance on when to use this tool over alternatives, prerequisites, or exclusion criteria. No explicit 'when not to use' is given.
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 provided; description does not disclose side effects, authorization needs, rate limits, or whether actions are destructive. Merely lists actions without behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with key information front-loaded. Efficient use of words, but could be slightly more informative without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Missing output schema, return value descriptions, prerequisites, or workflow guidance. For a tool with 4 parameters and multiple actions, the description is too sparse to fully guide usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 50% coverage; description adds context by naming the actions and relating sentiment/agent to the tool's purpose. However, 'topic' parameter remains unexplained, and no details on format or constraints beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it's an interaction history tracker with three specified actions. It distinguishes from siblings by focusing on social interactions, supported by the name 'social'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus the many sibling tools (e.g., chimera_memory, chimera_claims). Lacks context for when each action is appropriate.
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?
Given no annotations, the description partially discloses behavior: it checks confidence, forbidden capabilities, and hallucinations. However, it does not explain what happens on fail (e.g., blocking vs warning), nor does it mention the 'strict' parameter's effect on exception versus warning behavior, leaving gaps in understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence with no waste. It efficiently conveys the core action and key checks, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's complexity (9 parameters, no output schema), the description is brief and omits return value details beyond 'pass/fail with audit trace'. It does not explain audit trace content, usage context, or how the constraint middleware integrates with other tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-level information beyond the input schema. With 67% schema description coverage, some parameters lack descriptions (e.g., tool_name, detect_strategy), and the tool description does not compensate for these gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool applies constraint middleware, checking confidence, forbidden capabilities, and hallucinations, returning pass/fail with an audit trace. It is specific about the resource and action, but does not distinguish from sibling middleware tools like chimera_safety_check or chimera_detect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 description lacks context about prerequisites, when not to use, or how it differs from sibling tools, which is critical for a middleware tool among many similar ones.
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 disclose all behavioral traits. It mentions confidence aggregation and trace history, but fails to specify side effects (e.g., whether original envelopes are modified), idempotency, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that immediately conveys the core purpose. No filler or redundancy; every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given 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 is insufficient. It omits details on merge strategies, return format, edge cases, and constraints, leaving the agent with significant ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 25%, most parameters (strategy, merge_value_mode, namespace) lack explanatory comments in both schema and description. The description only hints at envelopes; it does not define the merge strategies or the meaning of namespace.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (merge), the resource (result envelopes), and the outcome (aggregated confidence and trace history). It is specific and distinguishes the tool from siblings by focusing on merging envelopes with provenance tracking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other chimera tools. It does not mention prerequisites, exclusions, or alternatives such as chimera_trace or chimera_summarize.
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 provided, so description must fully disclose behavior. It mentions tracking state and actions including reset, but doesn't explain side effects, limits, or whether actions mutate state persistently.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with clear, front-loaded purpose. No wasted words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, and description fails to mention return values or output structure. Mentions tracked attributes but not what the tool actually returns, leaving a critical gap for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 80% with decent parameter descriptions. Description adds context linking parameters to actions and state, but doesn't significantly enhance understanding beyond what schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it is a 'Sensor/action state simulator' with listed actions and tracked state variables, distinguishing it from sibling tools like chimera_audit or chimera_knowledge.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives; lists actions but no context for selection among many sibling 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?
With no annotations, the description discloses the iterative process of selection and mutation and the return format. However, it does not mention side effects, determinism, or whether the operation is read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. Front-loaded with the main purpose: 'Fitness-ranked candidate selector.' Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description omits the 'action' parameter which has two modes (run/info). No output schema, so the return explanation is minimal. Lacks details on prerequisites, error conditions, or parameter interactions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 80% (4 of 5 parameters have descriptions). The description adds context about 'N generations' and 'mutation' but does not explain the 'action' parameter or the candidates structure beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a fitness-ranked candidate selector that runs evolutionary generations, distinguishing it from other chimera tools like chimera_score or chimera_optimize. The verb 'selects' and resource 'candidates' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like chimera_optimize or chimera_explore. The description implies it is for evolution but does not state exclusions or prerequisites.
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 provided, the description carries the full burden. It states the core behavior (computing ECE), but does not disclose behavioral traits such as input validation requirements, handling of empty predictions, side effects, or performance characteristics. This is insufficient for a tool with no annotation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, no redundant phrases, and front-loads the key purpose. Every word adds value, making it efficient for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, the description should clarify what 'overconfidence/underconfidence rates' means (e.g., dictionary of floats, thresholds). It also omits details on default values, error handling, and edge cases for empty or malformed input, leaving the agent with incomplete context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, and the description adds clarity by explicitly stating the structure of 'predictions' as a list of objects with 'predicted_confidence' and 'was_correct'. However, the 'label' parameter is only described by its default in the schema, and the description adds no additional semantics for it, resulting in moderate value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool computes calibration error (ECE) from predicted confidence and correctness, and returns overconfidence/underconfidence rates. It uses a specific verb ('compute' implied) and resource (calibration error), and distinguishes from sibling tools that handle other aspects like audit or confidence.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like chimera_confident or chimera_self_model. There is no mention of prerequisites, context, or exclusions, leaving the agent without decision support for tool selection.
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?
Without annotations, the description partially fills the gap by mentioning output features (typing, tagging, provenance), but it does not disclose side effects, authentication needs, rate limits, or state modification. It provides moderate transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 15-word sentence, efficiently front-loading the core action and key features. It is concise but could be slightly improved with structural breaks for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no annotations, the description fails to cover expected output format, parameter dependencies (text vs envelope), or error conditions. It leaves significant gaps for an agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 75% (3/4 params have descriptions). The description adds value by grouping 'text or an envelope' as primary inputs but does not detail envelope type, max_claims significance beyond 'maximum', or namespace usage. It adds moderate context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Extract' and the clear resource 'atomic claims', and distinguishes the tool from siblings like 'chimera_detect' or 'chimera_causal' by focusing on claim extraction with typing, tagging, and metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 vs alternatives (e.g., chimera_detect). It does not explain prerequisites or scenarios where this tool is preferred.
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. Description discloses return type (flags and signals) and lists strategies, but does not detail side effects, permissions, or limitations. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundancy. Efficiently conveys purpose and key details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, complex nested params, and multiple strategies. Description omits output format, combination rules, and interpretation of flags. Incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50%. Description adds minimal value beyond schema: lists strategy names and params structure is already in schema. No extra context for 'value' or 'confidence'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'detect', resource 'hallucination and MCP security', and distinguishes from siblings by focusing on detection of specific threats. Lists strategies and outputs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like chimera_audit or chimera_safety_check. Does not specify when not to use or how to choose between strategies.
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 discloses that the tool transforms text and returns token savings, but does not cover permissions, side effects, or whether input is mutated. The brief description provides basic behavioral context but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence (14 words), front-loading the core operations. Every word is informative, with no redundancy. It is appropriately sized and structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given five parameters, no output schema, and many sibling tools, the description is insufficient. It omits details on return structure, algorithm selection, and the 'focus' parameter's role, leaving gaps for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does 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 no additional meaning beyond the schema; it lists operations that map to strategies but does not explain 'focus' or 'algorithm' parameters, nor their interaction.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 specific verbs and resources: 'Remove filler, deduplicate sentences, normalize whitespace from text.' It also mentions the return value ('optimized text and token savings'), distinguishing it from siblings like chimera_compress or chimera_summarize.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs. alternatives such as chimera_compress or chimera_dedup_lookup. The description only lists operations, leaving the agent to infer context without explicit scenarios 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 reveals the core behavior (confidence-weighted consensus) and outputs, but does not explain edge cases (e.g., ties, invalid confidence values, empty responses) or the role of the timeout parameter. With no annotations, more detail is needed for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences that front-load the core function and outputs. Every word adds value, with no redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with nested objects and a timeout parameter, the description is minimally adequate. It covers the high-level purpose and outputs but omits details on response format, parameter behavior, and error handling, leaving gaps for an agent to operate correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add meaning to the parameters beyond what the schema provides. It fails to explain the nested object structure (answer, confidence, latency_ms) or the timeout parameter. Given 0% schema description coverage, the tool description should compensate but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: a confidence-weighted consensus vote across agent responses. It explicitly mentions the key outputs: winner, confidence, and contradiction count, making the function 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like chimera_score or chimera_deliberate. It lacks context on prerequisites or scenarios where this tool is most appropriate.
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 mentions return values (emitted values, confidence scores, gate logs, assertion results) but does not disclose side effects, execution limits, authentication requirements, or error behavior. With no annotations, more detail would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the core purpose and output. It is concise without being under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and no output schema, the description covers the main functionality. However, it lacks details on execution constraints, state changes, or potential errors, which would be useful for a run tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the 'source' parameter described as 'ChimeraLang source code'. The description adds no further semantic information beyond what the input schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Execute' and the resource 'ChimeraLang program', and it distinguishes the tool from siblings like chimera_audit or chimera_batch by indicating it runs a program rather than auditing or batching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., chimera_batch for batch execution or chimera_audit for analysis). The context of use is only implied.
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 fully disclose behavior. It explains the pass/fail outcomes but does not mention side effects, idempotency, or whether it is read-only. For a simple assertion, this is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately communicates the tool's purpose and results. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple assertion tool with three parameters and no output schema, the description is complete enough. It covers the core logic and return types, though it could optionally mention that the value is returned on pass.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter thoroughly documented. The description adds no new semantic information beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: assert value confidence >= 0.95, and specifies the two return outcomes (ConfidentValue on pass, ConfidenceViolation on fail). It distinguishes from sibling tools by its specific focus on confidence assertion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like chimera_constrain or chimera_verify. The description is purely functional without context for selection.
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 mentions return format and stop_on_error parameter, but does not explain if calls execute sequentially or in parallel, any limits on batch size, or potential side effects. This leaves significant gaps for a batch execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with the core purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of output schema and annotations, the description provides the basic input/output behavior but lacks details on execution model, error handling scope, and scalability considerations. For a batch tool, more completeness is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The tool description does not add additional parameter semantics beyond what the schema already provides; it only summarizes the main benefit. The schema descriptions are sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Execute multiple chimera tools in one call', which is specific and distinguishable from the many sibling tools that operate on single tasks. The mention of saving tokens and returning results in call order adds clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (saving tokens vs separate round-trips) but does not explicitly mention when not to use or provide alternatives. The sibling tools are individual, so the usage is fairly obvious.
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 reveals key behavioral details: rule-based processing, checks on four ethical principles, and outputs a score plus recommendation. With no annotations, this is sufficient transparency for a simple evaluation tool, though it could mention limitations 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two crisp sentences with no filler. It front-loads the purpose and immediately lists the principles and outputs. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given only one parameter and no output schema, the description covers the core functionality. However, it does not specify the output format (e.g., score range, recommendation text) or any edge cases, which would improve completeness for an evaluation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single 'action' parameter already described. The description adds context that the action will be evaluated against ethical principles, which adds some meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states this tool performs rule-based ethical scoring of an action, listing the four principles (non-maleficence, autonomy, justice, beneficence) and the return of a score and recommendation. This specificity distinguishes it from sibling tools like chimera_safety_check or chimera_verify.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 (e.g., chimera_deliberate, chimera_safety_check). The context is only implied by the name and description, but no when-not-to-use or comparison is provided.
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 the description must carry behavioral info. It explains the pipeline steps and return values, but does not disclose side effects, auth needs, or whether data is mutated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that front-load the purpose and return values. Every part is informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 params, no output schema, and no annotations, the description explains the pipeline and return fields but lacks detail on return types or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does 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 parameter meaning. The description adds no extra details beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'full pipeline' combining optimization, compression, and budgeting, and specifies three return values. This distinguishes it from sibling tools that perform only individual steps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when an integrated pipeline is desired, but does not explicitly state when to use this tool vs alternative siblings or provide exclusions.
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 provided, the description carries the full burden of transparency. It states the output but omits details about side effects, authentication, rate limits, or behavior when the threshold is not met. This partial disclosure is insufficient for a tool that processes multiple inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences that front-load the purpose, list strategies, and mention output. Every word earns its place, with no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 3-parameter schema and absence of output schema, the description partially explains the return (winner and divergence score) but does not specify types or behavior when consensus fails. Some edge cases and details are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 67% of parameters (candidates and threshold). The description adds value by listing all three strategies explicitly, which is not in the schema (only enum values). It also clarifies the output, aiding understanding of parameter purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: collapsing multiple candidates into a consensus result. It specifies the available strategies (majority, weighted_vote, highest_confidence) and the output (winner and divergence score). This effectively 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives. It lists strategies but lacks when-not or usage context, leaving the agent to infer appropriate scenarios.
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. It discloses the estimation purpose and benefit, but does not cover behavioral traits such as accuracy, performance impact, or whether the estimate is real-time or cached. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines the tool's action and inputs, second explains the value proposition. Highly concise, front-loaded, and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, inputs, and motivation but lacks information about the output format or return value. No output schema exists, so the description should hint at what the estimate looks like. Adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67% (two of three parameters have descriptions). The description does not add meaning beyond the schema; system_prompt lacks a schema description but the tool description implies its role. Baseline 3 with no extra semantic detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates per-turn baseline cost from specific sources (system prompt, tool definitions, MCP servers). Uses specific verb 'estimate' and resource 'per-turn baseline cost', and distinguishes from siblings by focusing on overhead/ghost tokens.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when wanting to understand and reduce overhead costs, but does not explicitly state when to use vs alternatives like chimera_cost_estimate or chimera_cost_track. No exclusions or conditional use cases provided.
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 return structure (safety verdict, reason, attack flags, category counts) and mentions pattern-based approach, but does not state whether the tool is read-only, requires special permissions, or has side effects. Assumed non-destructive for a check tool, but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two compact sentences: first states purpose, second lists returns. No unnecessary words, front-loaded effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has moderate complexity (2 params, no output schema). The description covers purpose and returns but lacks details on parameter behavior (e.g., namespace usage), output format, or usage constraints. Adequate but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (content has description, namespace has default only). The description adds 'pattern-based' context but no parameter-specific details beyond schema. Baseline is 3 as coverage is not low (<50%).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'pattern-based content safety check plus MCP security attack-pattern detection'. It specifies the verb (check, detect), resource (content), and the distinct combination of safety and security analysis, which distinguishes it from sibling tools like chimera_gate, chimera_detect, or chimera_verify.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for content safety and attack-pattern detection but does not explicitly provide when-to-use or when-not-to-use guidance relative to alternatives. No exclusions or alternative tool references are given.
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. It states the tool is safe and automatically called by the Stop hook, but does not detail side effects, mutability, or behavior with different parameters. Given the lack of annotations, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. The first sentence lists outputs, the second provides safety and usage notes. It is front-loaded and each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple reporting tool with only two parameters (both with defaults) and no output schema, the description covers the essential aspects: what it returns, when to call it, and that it is safe. It could be improved by mentioning the output format, but it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the 'namespace' or 'include_dedup' parameters at all. It only lists outputs. The description adds no meaning beyond the schema, leaving the agent unable to determine what these parameters control.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides an 'End-of-session summary' listing specific items (tokens saved, dedup cache hits, top compressed responses, lock state). This is a distinct verb-resource combination that differentiates it from siblings like chimera_audit or chimera_dashboard.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Safe to call any time; the Stop hook calls it automatically when the agent stops responding.' This gives clear context on when to use it (any time) and a caveat about automatic invocation. It does not explicitly exclude alternatives, but the guidance is sufficient for basic use.
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. It describes the optimization, cost estimation, budget proposal, and the approval workflow. However, it does not disclose potential side effects, storage, or rate limits, which are typical for such a tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences covering the core workflow. It is front-loaded with the key directive 'CALL FIRST on every message.' Could be more structured, but it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description implies return fields (proposal_text, optimized_prompt) but does not describe the full return structure or error handling. For a complex tool with multiple outputs, this is a gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter is already documented in the input schema. The description focuses on workflow rather than adding parameter-level meaning. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: it optimizes input, estimates token cost, and proposes a budget. It emphasizes 'CALL FIRST on every message,' distinguishing it from other chimera tools that handle later stages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: call this tool first on every message, and after approval, constrain the response and use the optimized prompt. It does not explicitly list when not to use it, but the workflow is clear.
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 carries the full burden. It only states that the value is marked unverified, which is a core behavior, but it lacks details on side effects, permissions, or what happens to the value. The description is too brief 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with no wasted words, but it may be too short for a tool with no annotations and no output schema. It is front-loaded but could benefit from slightly more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (3 params, no nested objects) and the absence of an output schema, the description is somewhat complete: it explains the core operation. However, it does not mention the return value or any additional effects, leaving some gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameters are documented. The description adds useful context for the confidence parameter ('typically low for explore values'), which goes beyond the schema. However, it adds no new meaning for 'value' or 'label'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool wraps a value as an Explore marker for unverified data, which distinguishes it from siblings like chimera_verify. The verb 'wrap' and resource 'value' are specific, and the context of hypotheses and brainstorms aligns with the tool's role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear use case ('Use for hypotheses and brainstorms') but does not explicitly state when not to use or name alternatives. However, the sibling tool names suggest alternatives like chimera_verify or chimera_confident, providing implicit guidance.
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?
Without annotations, the description carries the full burden of disclosure. It states the tool is non-executing and validates certain rules, but lacks details on return values, error handling, side effects, or required permissions. The description adds moderate value beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence conveys the tool's core function and key differentiators without any wasted words. The structure is front-loaded with the main action ('Static type-check') immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the essential purpose. However, it does not explicitly mention what the tool returns (e.g., error messages or success indicators), which would improve completeness. Slightly lacking for full contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage for the single parameter 'source' is 100%, so the schema already explains what it is. The tool description does not add additional semantics about the parameter's format, expected length, or examples, making it minimally sufficient but not enhanced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs static type-checking on a ChimeraLang program without execution. It specifies validation of confidence boundaries and scope rules, distinguishing it from execution-focused tools like chimera_run and verification tools like chimera_verify.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The description implies it should be used before execution, but does not mention alternatives or contexts where other sibling tools (e.g., chimera_safety_check, chimera_verify) would be more appropriate.
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 the full burden of behavioral disclosure. It mentions that the cache is 'Populated automatically by the PostToolUse hook,' implying side effects from other tools. However, it does not elaborate on the consequences of the 'clear' action (e.g., affecting dedup behavior) or any rate limits, persistence, or reversibility. This is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: three sentences covering all essential information. It is front-loaded with the purpose, followed by action-specific guidance and a note on population. No redundant or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 parameters, no output schema, and no annotations. The description covers the core functionality and action semantics, but does not describe expected output (e.g., format of 'list' results) or the full impact of 'clear' on subsequent dedup behavior. Given the simplicity of the tool, this is adequate but leaves gaps in understanding the return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (2 of 4 params have descriptions in the schema). The description adds context: it explains the 'action' enum values and states that 'key' is a 16-char hex required for action=get. It does not add detail for 'tool_name' or 'namespace', leaving half the parameters with only schema-level info. The description partially compensates but still lacks full coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Inspect or query the per-namespace tool-call dedup cache.' It specifies three distinct actions (get, list, clear) with their purposes, making the tool's functionality unambiguous. This is further supported by listing the actions with their usage in the same sentence, distinguishing the tool from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance for each action: use 'get' with a key to retrieve metadata, 'list' to see all tracked calls, 'clear' to reset. It clearly indicates when each action is appropriate. However, it does not explicitly state when not to use the tool or mention any alternatives, though the sibling list does not contain a close alternative. A small gap in exclusions prevents a 5.
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 mentions reduction metrics and zero diagnostic loss, but lacks details on where compressed logs go, side effects, or recording behavior beyond auto_track.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the purpose and provide key details without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While covering main functionality, the description omits what the tool returns (output format), which is important given no output schema is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%. The description adds meaning by mentioning head/tail windows and preserved patterns, but does not explain parameters like auto_track, model, or namespace, leaving gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compresses logs while preserving errors, warnings, tracebacks, and head/tail windows. It uses specific verbs and resource, distinguishing it from sibling tools like chimera_compress.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies the use case for build/test/install logs, providing clear context. However, it does not explicitly mention when not to use it or list alternative tools.
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. It discloses that the tool is lossless, adds cache markers to returned blocks, and returns blocks ready for the SDK system array. It could mention idempotency or side effects, but it is fairly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences and front-loaded with the primary action. Every sentence adds value—purpose, return format, and benefit—earning its place without verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description explains what the tool returns (blocks with cache_control) and the key parameter behavior. It covers the essential use case and benefits, though it could briefly explain the internal caching mechanism.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds minimal extra meaning beyond the schema (e.g., clarifies that stable=true makes a block eligible for caching). Baseline 3 is appropriate as the schema already documents parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Build Anthropic prompt-cache markers for stable text blocks' with a specific verb and resource. It differentiates from siblings by focusing on caching markers for stable text, which is distinct among many chimera tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for stable text blocks that recur every turn, noting 75-90% token savings. However, it does not explicitly state when not to use it or name alternative tools, leaving usage guidance somewhat implicit.
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 exist, so the description carries full burden. It discloses the tool does not make API calls, which is good, but lacks details on accuracy, limits, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise—two sentences covering purpose, key feature (no API call), and supported models. No filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple estimation tool, the description is largely complete. It covers what, how (no API call), and supported models. However, it does not mention that cost estimates are approximate or any caveats.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description does not add extra meaning beyond the schema. Baseline 3 is appropriate as the schema already documents all parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates token count and USD cost for text or messages, specifies it makes no API call, and lists supported model families (Claude, GPT, Gemini). This distinguishes it from sibling tools like chimera_cost_track (actual cost tracking) and chimera_budget (budget management).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context (estimates without API call, supports specific models) but does not explicitly state when not to use or mention alternatives. It implies usage for cost planning before actual API calls.
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 states 'Log before/after token counts', indicating a write operation. Though not fully detailed, it is clear and non-contradictory. A minor gap is not explaining persistence 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the core action and resource. No wasted words. Efficient and direct.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a logging tool without output schema or annotations, the description adequately explains the purpose and mentions a companion tool (chimera_dashboard) for viewing. It is nearly complete, though could note return behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so all parameters are described in the input schema. The description adds no extra parameter context beyond what the schema provides, earning baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Log before/after token counts to the session cost tracker', specifying the action and resource. It also directs to 'View with chimera_dashboard', distinguishing it from sibling tools like chimera_cost_estimate or chimera_dashboard.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for logging cost data but provides no explicit guidance on when to use versus alternatives, such as chimera_cost_estimate for prediction. No exclusions or context for when not to use.
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 description carries the burden. It discloses a key behavioral trait: 'Lossy by design: reconstructs meaning, not surface form'. This adds value beyond schema and helps set expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and lossy nature. Every sentence earns its place. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 100% schema coverage and no output schema, the description is fairly complete. It explains purpose, usage timing, and key behavioral trait. Could mention return format or limitations but acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%. Both parameters are fully described in the schema. The description does not add meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb and resource ('Translate Chimera Glyph text back into readable English') clearly state the tool's function. Lossy nature is mentioned. However, it does not differentiate from sibling tool 'chimera_glyph_directive'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'at the end of an AI-internal CG reasoning chain'. No exclusions or alternatives mentioned, but context is clear.
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 states the tool returns a tool subset, which is a safe read operation. No side effects or destructive actions are implied. However, it doesn't elaborate on the format or behavior beyond returning a list, so it's adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of exactly two sentences, with the purpose front-loaded. Every word is informative, no fluff or repetition. It is highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description could specify the return format (e.g., list of tool names) but it's not strictly necessary. The tool has only 2 parameters with defaults, and the description covers its purpose and usage context. It is largely complete for the simplicity of the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already provides good descriptions for both parameters (mode enum with explanations, task_description optional). The tool description adds the context of reducing token overhead but doesn't enhance individual parameter semantics beyond what's in the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and resource ('relevant tool subset for a task type'), clearly indicating what the tool does. It distinguishes itself from sibling tools by being a mode selector that returns a subset of tools based on a task type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear reason to use the tool: 'to avoid unnecessary tool invocations and reduce token overhead.' While it lacks explicit 'when not to use' or alternatives, the context of many sibling tools implies this is a routing tool, and the description gives sufficient usage 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?
Despite no annotations, description discloses it is LLM-free, uses TF-IDF, and automatically records token savings to chimera_dashboard with an option to disable (auto_track). No descriptions of destructive effects or rate limits, but the side effect of tracking is well documented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. Each sentence adds value: first states core functionality, second explains side effect and usage recommendation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the return format (likely a string of sentences) is not described, leaving ambiguity. However, for an extractive summarizer, the output is intuitive. The tracking side effect is well explained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents parameters. The description adds context about the auto_track and model mapping to dashboard, but doesn't provide significantly deeper meaning beyond what the schema already offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it's an 'LLM-free extractive summarizer' that 'ranks sentences by TF-IDF and returns top N' with explicit usage guidance ('Use before passing long docs to other tools'), distinguishing it from the many other chimera tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for when to use ('before passing long docs to other tools') and mentions the auto_track feature for optional behavior, but does not explicitly state when not to use or name alternatives.
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: default mode, thresholds (60% stance, 0.62 similarity), detection conditions, speed trade-offs, and that it provides a numeric divergence score. It lacks mention of side effects or 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly dense with useful information front-loaded. Every sentence contributes value, though it could be slightly more streamlined without losing context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists; the description mentions reporting consensus_detected and a divergence score but does not fully specify the response structure. For a 3-param tool, this is a notable gap, though the description provides enough for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 33% (only mode described). The description adds meaning by explaining how prompt and perspectives are used in deliberation (stance detection, term alignment, overlap). Mode options are detailed beyond enum labels.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Multi-perspective deliberation' and explains that it detects consensus across perspectives. It distinguishes two modes and contrasts with direct reasoning, making the tool's unique value evident among many chimera siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on when to use each mode (lexical_consensus for controlled vocabulary, semantic for general) and contrasts with direct reasoning. However, it does not explicitly list when not to use this tool or compare to specific sibling tools.
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?
Without annotations, the description conveys the tool's effect (forces CG output) and output nature (directive string). Clearly states the directive must be injected as a system message. No contradictions; transparency is good though not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, no wasted words. Structure efficiently guides usage and links to sibling tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description adequately explains output as a directive and its injection point. Could slightly benefit from noting immediate use but is sufficiently complete for a directive-generation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline is 3. Description adds value by explaining the default and effect of 'style' parameter, and clarifies 'task_hint' is appended. However, much of this is redundant with schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool emits a system instruction forcing AI to write in Chimera Glyph, specifying the directive's role and distinguishing it from chimera_glyph_translate which handles translation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs the agent to inject the returned directive as a system message and explains the subsequent workflow: AI produces CG output, then translation via sibling tool. Lacks explicit when-not-to-use scenarios but provides sufficient context.
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 discloses key behavior: the tool is read-only and works offline. This informs the agent of safety and network independence, though it could add details about error handling or data volume.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence with the purpose and a list of actions, plus the read-only/offline tag. Every sentence serves a purpose, and key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, no output schema), the description adequately covers the basics. It could be slightly more specific about each action's result, but remains complete enough for an AI agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'action' is an enum, and the description lists its four possible values, adding meaning beyond the raw schema. However, it does not explain what each action returns or how to interpret outputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to inspect bundled material packs and manifests. It lists the specific actions available (list_packs, status, licenses, source_manifest) and distinguishes the tool from siblings by focusing on materials and being read-only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for inspecting materials and notes read-only and offline behavior, but does not explicitly state when to use this tool versus other chimera tools, nor does it provide conditions for using each action.
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 covers core behavior: execution, proof generation, and outputs. It lacks details on error handling or resource usage but is sufficient for understanding the tool's primary actions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences with no wasted words; the first sentence captures the core action and output, the second provides value by comparing to an alternative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and lack of output schema, the description adequately explains inputs and outputs (results, hash chain, root hash, verdict). Slightly more detail on the output format would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the sole parameter 'source' (ChimeraLang source to prove). The tool description does not add new semantic information beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (execute, generate) and resource (ChimeraLang, Merkle-chain proof), with a distinct cryptographic focus that differentiates 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly contrasts with 'direct reasoning', explaining when to use this tool for auditable, tamper-evident proofs, but could be more specific compared to similar chimera tools like chimera_verify.
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?
Without annotations, the description conveys key behaviors: it returns remaining_tokens and status (ok/warn/critical), and instructs compression when critical. This goes beyond basic locking, though it could detail side effects or error scenarios.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, front-loaded with the primary purpose, then lists actions, returns, and a conditional behavior. Every sentence adds distinct value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, 100% schema coverage, and no output schema, the description covers all actions, return values, and a critical behavior. It lacks output schema details but that is not required. Adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning: it connects max_output_tokens to chimera_csm, explains tokens_generated as 'this turn', and clarifies action enum values. This enhances understanding beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool manages token budgets after CSM proposal approval, with four distinct actions (lock/check/update/release). It distinguishes itself from siblings like chimera_budget by focusing on post-approval locking, making purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates the tool is used 'after user approves CSM proposal' and lists available actions, providing clear context. However, it does not explicitly specify when to use this tool over alternatives like chimera_budget, leaving some ambiguity for an AI agent.
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?
Discloses automatic token tracking to chimera_dashboard with disable option, and explains quantum algorithm's preservation of important content via structural salience. No annotations present, so description carries full burden; covers compression outcomes and 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: three sentences cover all essential aspects without redundancy. Front-loaded with main action, then key details, then comparisons. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers algorithms, levels, side effects, parameter usage. Lacks explicit output format details (beyond 'compressed text and ratio') and reversibility, but overall adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 8 parameters are described in schema (100% coverage). Description adds valuable context: explains compression levels, the focus parameter for quantum mode, and the auto_track/dashboard integration. Exceeds baseline of 3 by providing operational meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool compresses text via contractions/symbols, with specific levels (light, medium, aggressive). Distinguishes itself from manual regex replacement and implicitly from other chimera tools by mentioning quantum algorithm and structural salience.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance to prefer over manual regex replacement and explains when to disable auto_track. Mentions quantum vs classic algorithm choices but lacks explicit exclusions relative to sibling tools like chimera_log_compress.
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 scoring behavior (mode-dependent, O(n) efficiency) and scoring range. Minor gaps: no mention of error handling or behavior when focus is missing in importance_for_goal mode, but the schema indicates it's required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each containing essential information. It is front-loaded with the core purpose and uses no unnecessary words, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (two modes, O(n) advantage) and no output schema, the description is sufficient for an agent to understand usage and behavior. It could optionally mention the return format, but the tool name implies scores.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does 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 extra meaning: it explains mode semantics in detail and clarifies that focus improves drop_priority scoring. This goes beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: scoring messages 0-1 for context-window management. It distinguishes two modes (drop_priority and importance_for_goal) and explains their use cases, making it distinct from sibling tools like chimera_compress or chimera_summarize.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use each mode (drop_priority for compression eviction, importance_for_goal for relevance retention) and compares to direct reasoning with a cost advantage. This helps an agent decide between modes and avoid alternatives.
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 provided, so description carries full burden. It explains verdict types (lexically_supported/contradicted/insufficient), method details (Jaccard token-overlap, deterministic), optional RAG behavior, and method options including dependencies and non-determinism for 'llm'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured with front-loaded purpose and important caveat. Some repetition (e.g., 'lexical token-overlap' mentioned twice) but generally efficient. Slightly longer than minimal but justified by detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters, high schema coverage, and no output schema, description fully covers tool behavior: verification methodology, RAG, multiple methods, and important constraints. Completeness is excellent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 88% (high), baseline 3. Description adds context beyond schema: explains how 'corpus' enables RAG, 'retrieve_k' behavior, and 'method' options with their characteristics. This adds meaningful guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'verify', resource 'claims against evidence', and method 'lexical token-overlap scoring'. Distinguishes from sibling 'chimera_constrain' and contrasts with 'direct reasoning'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (verify claims), warns about limitation ('not semantic entailment or NLI'), suggests alternative ('Supplement with chimera_constrain for semantic checks'), and contrasts with direct reasoning.
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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