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nano-step

embrace-raw-readonly

by nano-step
OverviewSchemaRelated ServersScoreDiscussions
Python
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one lists available tools, the other invokes a specific tool. There is no overlap or ambiguity in selecting between them.

    Naming Consistency4/5

    Both tools start with 'embrace_' and include 'readonly', but one is 'list_readonly_tools' (verb_noun) while the other is 'call_readonly' (verb_adjective). The pattern is mostly consistent but not perfectly parallel.

    Tool Count2/5

    With only two tools, the surface is thin. However, this is a deliberate thin proxy layer for a remote readonly API, so the minimalism is justified, but it still falls below the typical well-scoped range.

    Completeness5/5

    The two tools form a complete interface for interacting with the remote readonly toolset: listing available schemas and calling them. There are no missing operations within the stated scope of acting as a proxy.

  • Average 3.9/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 5 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

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

    With no annotations, the description is the sole source of behavioral information. It correctly implies a read operation and states the return format (full JSON), but it does not disclose any other behaviors such as potential size limits, whether all read-only tools are included, or if there are any side effects. For a simple listing tool, this is adequate but minimal.

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

    Conciseness5/5

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

    A single sentence that is front-loaded and carries no fluff. Every word contributes to the tool's purpose.

    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?

    The tool has an output schema and zero parameters, so the description covers the essential purpose. It might mention that it is the authoritative source for schemas, but given the low complexity and presence of the output schema, the description is nearly complete.

    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 tool has zero parameters, so the description needs no per-parameter explanation. Baseline for zero parameters is 4, and the description adds no irrelevant information about 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 states a clear verb ('Return') and specific resource ('official Embrace read-only tool schemas as full JSON'), making it obvious what the tool does. It is distinct from the sibling embrace_call_readonly, which presumably calls a specific tool rather than listing schemas.

    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 gives no guidance on when to use this tool versus embrace_call_readonly or any other alternative. It does not explain typical use cases or prerequisites, leaving the agent to infer when listing schemas 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?

    No annotations are provided, so the description bears the full burden. It discloses that it accepts arbitrary JSON arguments and returns the complete JSON-RPC result, which is useful. However, it doesn't mention any side effects, error behaviors, or confirm that it only calls read-only tools (implied by the name). This is a moderate transparency gap given the lack of annotations.

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

    Conciseness5/5

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

    Two sentences, front-loaded with the core purpose, and both sentences earn their place. The structure is clean and efficient, with no fluff or repetition.

    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 the output schema likely covers return values, the description omits the apparently important fact that this tool is restricted to read-only operations (suggested by the name and sibling). It also doesn't mention error handling or prerequisites beyond discovering arguments. For a generic dispatcher, this is adequate but not comprehensive.

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

    Parameters3/5

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

    Schema description coverage is 0%, so the description must explain parameters. It explains the 'arguments' parameter well (arbitrary JSON) but does not elaborate on 'tool_name' beyond what the schema already shows. The description partially compensates but not fully, especially since tool_name is required and its purpose is only implied.

    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 calls one published Embrace tool and returns the JSON-RPC result. It distinguishes itself from the sibling by emphasizing it's a dispatcher, not a listing tool. A slightly higher score is withheld because it doesn't explicitly contrast with embrace_list_readonly_tools in terms of purpose, but the intent is unmistakable.

    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 gives explicit guidance: use embrace_list_readonly_tools first when arguments are unknown. It also explains why arbitrary arguments are accepted (schemas evolve independently), which informs when this tool is the right choice. This is clear and actionable usage direction.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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