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base76-research-lab

cognos-session-memory

by base76-research-lab
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: load_session retrieves context and save_session stores it. There is no overlap in their functionality, making it easy for an agent to select the correct one.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (load_session, save_session), which is clear and predictable. No mixing of conventions.

    Tool Count3/5

    With only 2 tools, the surface is thin for a memory management system. While it covers the basic load/save operations, the count is borderline low for the implied scope.

    Completeness3/5

    The tool set covers loading and saving sessions, but lacks operations like list, delete, or update sessions. There are notable gaps that may require agents to work around missing functionality.

  • Average 4.3/5 across 2 of 2 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • 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.

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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

  • Behavior4/5

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

    No annotations provided, so description carries full burden. It discloses that it only returns context passing trust threshold, never injects low-confidence or stale sessions, and returns summary and block. However, it does not specify behavior when no session exists 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?

    Two sentences with no redundancy. First sentence states action and expected output; second adds critical constraint. Fully front-loaded and efficient.

    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 optional parameter and no output schema, the description covers purpose, return values, and trust threshold. It is complete enough for an agent to use correctly, though it omits edge cases like missing session.

    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 new insight beyond the schema. It reinforces the threshold's role but does not elaborate on format or usage semantics.

    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 'Load' action on 'last verified session context from CognOS Session Memory' and specifies output: summary and inject-ready block. It distinguishes from sibling 'save_session' by verb and scope, and adds constraint about trust threshold.

    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?

    Description implies use for retrieving a verified session context but does not explicitly state when not to use or alternative tools. It mentions trust threshold but lacks exclusionary guidance such as 'use save_session to create a session'.

    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?

    With no annotations provided, the description fully carries the burden of behavioral disclosure. It reveals that summaries are 'epistemically scored', that low-scored summaries may not be injected next session, and that the operation saves to persistent memory. No contradictions noted.

    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 two compact sentences. The first sentence states the core purpose, and the second adds essential behavioral context. No redundant or unnecessary 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 output schema), the description is nearly complete. It explains the trust scoring mechanism and injection eligibility. However, it does not mention what the tool returns (if anything) or potential error conditions, which would be helpful but not critical for a save operation.

    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% with descriptions for both parameters, but the tool's description adds extra semantic value beyond the schema: it specifies the recommended word count range (100-200 words) and content guidelines for the 'summary' parameter ('active project, last decision, current output, open questions, key files'). The 'project' parameter is correctly noted as optional.

    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 'Save' and the resource 'trust-scored session summary to CognOS Session Memory'. It distinguishes from the sibling tool 'load_session' by implying the opposite action (save vs load), and also mentions an alternative ('/compact') for context.

    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 says when to use this tool ('instead of or after /compact to preserve verified context across sessions') and provides a guideline on summary quality ('short or vague summaries get lower trust scores and may not be injected next session'). It does not explicitly state when not to use it, but the context is clear.

    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 the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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