Hokmah

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

No annotations are provided, so the description must cover behavioral traits. It mentions the outputs and zero LLM token cost, but does not disclose safety (e.g., read-only nature), side effects, authorization needs, or rate limits. For a tool that likely performs analysis, this 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.

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

The description is very concise with two sentences front-loading the purpose and output. Every sentence is useful, though it could be slightly more structured. It earns a high score for minimal waste.

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

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

Given the complexity (3 params, no schema descriptions, no annotations) and presence of an output schema, the description is incomplete. It covers only the output but not parameter semantics or behavioral context, making it inadequate for correct tool selection and invocation.

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

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

Schema description coverage is 0%. The description does not explain the meaning or format of any of the three parameters (repo_url, query, branch). The schema provides names and types, but the description adds no value beyond that, leaving the agent without essential semantic context.

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

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

The description clearly states the verb 'analyze' and the resource 'impact of a code change', and specifies the outputs (risk score, affected files, related commits). It effectively distinguishes from sibling tools that focus on connecting projects or generating code.

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

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

The description implies usage for analyzing code change impact by stating what it does and highlights 'FREE — zero LLM tokens' as a benefit. However, it lacks explicit guidance on when to use or not use this tool versus alternatives, which is a gap.

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

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

With no annotations, the description carries the full burden. It only states the action without disclosing behavioral traits like error handling, idempotency, or side effects. The addition of 'FREE' is distracting and not functional.

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

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

The description is extremely short (one sentence plus 'FREE'), which is concise but sacrifices informative content. It is not well-structured with front-loaded key information.

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

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

Given the tool has four parameters (two required) and an output schema, the description provides no information about return values, usage, or setup steps. It is severely under-specified for a connection tool.

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

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

Schema description coverage is 0%, meaning no parameter descriptions in the schema. The tool description does not explain any of the four parameters (tenant, project, server_url, server_name), leaving the agent without meaning beyond the schema types.

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

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

The description clearly states the verb 'Connect' and the resource 'external MCP server to Hokmah', indicating the tool's purpose. It somewhat distinguishes from sibling tools like hokmah_connect_project by specifying 'external MCP server', but the differentiation is not strong.

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

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

No guidance is provided on when to use this tool versus alternatives (e.g., hokmah_connect_project). There is no mention of prerequisites, context, or when not to use it.

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

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

No annotations are provided, and the description does not disclose behavioral traits such as whether the tool modifies data, requires authentication, or has rate limits. The mention of 'FREE' is superficial.

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

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

The description is short with two front-loaded sentences. The first sentence conveys the main purpose; the second adds output specifics and a note. Some redundancy could be trimmed.

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

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

Despite having an output schema, the description does not explain return values, error handling, or prerequisites. For a tool building multiple graphs, more context on the process and results is needed.

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

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

Schema description coverage is 0%, and the description only mentions 'repo_url' implicitly via 'Connect a GitHub repo.' The 'branch' parameter with a default is not explained, leaving the agent to infer meaning.

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

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

The description clearly states the action 'Connect a GitHub repo to Hokmah' and specifies the output 'Builds TransitionGraph + IdeaGraph + WorldModel from commit history,' distinguishing it from siblings like 'hokmah_connect_mcp'.

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

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

No guidance on when to use this tool versus alternatives. The sibling tools 'hokmah_connect_mcp' and others are not referenced, leaving the agent to guess the appropriate context.

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

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

No annotations exist, so the description carries full burden. It mentions 'reduces hallucination via graph context' but does not disclose important behavioral traits such as error handling, resource consumption, state changes (e.g., file creation), or authentication failure behavior. The PRO note implies a cost but no details.

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

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

The description is very short (three phrases) and front-loaded with the core action. However, the structure is a list of disconnected statements rather than a cohesive paragraph. It is not verbose, but lacks essential information that could be added without increasing length significantly.

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

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

Despite having an output schema (removing need to explain return values), the description does not explain the tool's overall function in a complete way. Key aspects like the meaning of 'architectural memory', expected usage patterns, or relation to other tools are absent. The description feels incomplete for a tool with 4 parameters and a PRO label.

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

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

Schema description coverage is 0% (no parameter descriptions in schema). The tool description does not explain any of the four parameters (repo_url, query, branch, api_key), leaving the agent with no semantic understanding beyond property names. This fails to compensate for the missing schema descriptions.

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

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

The description states it 'Generate code with architectural memory', which clearly indicates the verb and resource. However, it lacks specificity about what type of code (language, purpose) and does not differentiate from the sibling tool hokmah_generate_tests, but the core purpose is adequately conveyed.

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

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

The description only mentions 'PRO — requires API key', hinting at a premium access condition but gives no guidance on when to use this tool versus the listed siblings (analyze, connect_mcp, connect_project, generate_tests). No contextual triggers or exclusions are provided.

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

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

No annotations exist, so description must fully disclose behavior. It mentions API key requirement and token efficiency but fails to state if generation is read-only or has side effects, rate limits, or failure modes.

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

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

Very short, but the key action is front-loaded. However, the '40x fewer tokens' claim and 'PRO' tagline are not essential for understanding usage, so the brevity sacrifices valuable detail.

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

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

With 4 parameters lacking schema descriptions and no guidance on usage context, the description is incomplete. Output schema exists but does not compensate for missing input semantics and when-to-use advice.

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

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

Schema description coverage is 0%, and the description only mentions 'api_key' as required. It does not explain 'query', 'repo_url', or 'branch', leaving the agent without meaning beyond parameter names.

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

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

The description clearly states the tool generates tests from the architectural graph, specifying the resource and action. It distinguishes from siblings like hokmah_generate_code and hokmah_analyze by focusing on tests, though 'test' meaning could be more explicit.

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

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

No guidance on when to use this tool vs alternatives like hokmah_generate_code or hokmah_analyze. The only usage hint is 'PRO — requires API key', which is a limitation, not a decision guide.

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