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ecestnrkl

figjam-context-mcp

by ecestnrkl
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TypeScript
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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct and non-overlapping purpose: ingest_board adds a board, get_board_context retrieves its context, and answer_from_board answers questions. No ambiguity in intent.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case: 'ingest_board', 'get_board_context', 'answer_from_board'. The naming pattern is uniform and predictable.

    Tool Count5/5

    With only 3 tools, the server is tightly scoped to a specific workflow (ingest, context, answer). Each tool serves a necessary step without unnecessary bloat.

    Completeness4/5

    The server covers the core workflow of ingesting a board, retrieving context, and answering questions. A minor gap is the lack of a tool to list or delete ingested boards, but this may be out of scope.

  • Average 3.7/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 16 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

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  • 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?

    No annotations are provided, so the description carries the burden. It discloses that the tool cites clusters and requires a previously ingested board, but does not cover permissions, rate limits, or mutability.

    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 concise sentence with no wasted words. However, it could be slightly more structured by including usage hints.

    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?

    With only 2 parameters and an output schema (not shown), the description covers the basic purpose, but lacks details on how citations are delivered or any edge cases. It is adequate but not comprehensive.

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

    Parameters2/5

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

    Schema coverage is 0%, so the description should add meaning beyond parameter names. It only says the tool answers a question about a board, but does not clarify that boardId refers to a valid board from a prior ingest or that question is free-form text. The names are self-explanatory but the description adds minimal value.

    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 answers a free-form question about a previously ingested board and cites clusters, distinguishing it from siblings like get_board_context (which likely provides raw context) and ingest_board (which is for ingestion).

    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 board must be previously ingested, but does not explicitly state when to use this tool vs alternatives, nor does it provide exclusions or prerequisites beyond 'previously ingested'.

    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 responsibility. It discloses that the operation returns text and clusters and requires a previously ingested board, but omits details on error handling, rate limits, or required permissions. It 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, well-structured sentence that places the key action and outputs first. Every word adds value, and there is no superfluous 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?

    Given the tool's simplicity (2 parameters, no annotations), the description is sufficiently complete. It explains the return type (text summary + clusters) and the optional scoping. The presence of an output schema further reduces the need for detail in the description.

    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% (only topic has a description). The description adds the phrase 'optionally scoped to a topic,' which clarifies the topic parameter's purpose. However, boardId lacks any description beyond being required, so the additional value is limited.

    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 returns a text summary and clusters for a previously ingested board, with optional topic scoping. It effectively distinguishes from sibling tools like answer_from_board and ingest_board by specifying the output type and prerequisite.

    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 should be used after a board has been ingested, but it does not explicitly state when to use this versus alternatives like answer_from_board. No direct guidance on prerequisites or context for selection 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?

    With no annotations, the description must fully disclose behavior. It explains that the tool reads, clusters, and caches data, but lacks details on side effects (e.g., is caching persistent? can it be redone?), authorization beyond token handling, or potential performance implications.

    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, moderately long sentence that efficiently conveys the core functionality. It avoids unnecessary words but could be slightly more structured (e.g., separate sentences for purpose vs. usage linkage).

    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 presence of an output schema (not shown but declared), the description does not need to detail return values. It covers the essential steps (read, cluster, cache) and links to sibling tools. Some missing detail on clustering meaning, but overall sufficient.

    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 itself provides full parameter descriptions (100% coverage). The tool description adds context about clustering and caching but does not enhance the meaning of individual parameters 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?

    The description uses specific verbs ('reads', 'clusters', 'caches') and clearly identifies the resource ('FigJam/Figma file'). It explicitly distinguishes from sibling tools by stating that the output is used for later 'get_board_context' and 'answer_from_board' calls.

    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 clearly indicates when to use this tool (as a prerequisite for the two sibling tools), providing clear context. However, it does not explicitly state when not to use it or mention alternative approaches.

    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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