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icohangar-ops

@cubiczan/chp-mcp

Server Quality Checklist

83%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct role: evaluate_spend_gate runs the policy check, approve_spend performs HITL approval, chp_content_hash computes hashes, and chp_version reports versions. No two tools overlap in purpose or could be easily confused.

    Naming Consistency4/5

    The names are consistent snake_case and mostly follow a verb_noun pattern (evaluate_spend_gate, approve_spend). The chp_ prefixed helpers break that pattern slightly, but the prefix clearly groups utility/version operations, so the overall convention remains predictable.

    Tool Count5/5

    Four tools is well-scoped for a narrow CHP Profile B protocol surface: gate evaluation, human approval, hashing, and versioning. Each tool earns its place without redundancy or bloat.

    Completeness4/5

    The core lifecycle is covered: evaluate → approve, with supporting hash and version utilities. A minor gap is the absence of an explicit tool to inspect proposal details, but the described results from evaluate_spend_gate include claims and content hashes, so agents can proceed without major dead ends.

  • Average 3.9/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • No commit activity data available
    • 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.

  • 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.

  • This repository includes a glama.json configuration file.

  • This server has been verified by its author.

  • Add related servers to improve discoverability.

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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 present, so the description carries the burden of behavioral disclosure. It adds useful constraints: only HITL_REQUIRED proposals are approvable, and BLOCKED / hard-rule failures are not. However, it does not state whether approval executes the spend, what side effects occur, what permissions are required, or what the return behavior is.

    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 filler. The key use condition and hard exclusion are stated immediately and clearly.

    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?

    For a tool with four parameters, nested objects, no annotations, and no output schema, this description is too sparse. It does not explain how to construct the action/policy payload, what a successful approval returns, or how to obtain the HITL_REQUIRED proposal in the first place.

    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 only 25% (just the approver field has a description). The tool description does not explain the action object, policy object, or committed_today semantics. Since schema coverage is low, the description needed to 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 states a specific action ('Human-in-the-loop approval') applied to a specific resource ('a proposal that returned HITL_REQUIRED') and explicitly excludes BLOCKED / hard-rule failures. This clearly distinguishes it from evaluative sibling tools like evaluate_spend_gate.

    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?

    It explicitly states when to use the tool (proposals that returned HITL_REQUIRED) and when not to use it (BLOCKED / hard-rule failures), with spec section references. It does not explicitly name an alternative tool, but the exclusion criteria provide strong situational 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?

    No annotations were provided, so the description carries the disclosure burden. It does disclose a key behavioral fact: hard policy violations cannot be overridden by a human. However, it does not state whether the tool mutates state, consumes budget/quota, requires authentication, or what happens on error, leaving notable gaps for a policy-evaluation 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?

    The description is two sentences, front-loads the core action and outcomes, and avoids filler. Every clause adds useful information: the gate type, the possible return states, the presence of claims plus content hash, and the hard-block caveat.

    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 gives enough for basic use but lacks some completeness for a nested-parameter tool with no output schema. It does not explain the distinction between LOCKED and BLOCKED, the shape of the claims, or the meaning of the content hash. The behavioral caveat helps, but the description is not richly complete given the complexity of the inputs.

    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 high: the top-level parameters action, policy, and committed_today each have descriptions. The tool description adds no additional parameter semantics beyond the schema, so the baseline 3 is appropriate. Nested fields like asset, notional, max_notional, and hitl_threshold remain self-describing from names but are not elaborated.

    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 ('Run') and names a clear resource ('CHP Profile B capital/spend gate on a proposed action'). It also lists concrete outputs (LOCKED, HITL_REQUIRED, or BLOCKED with claims and a content hash), which clearly distinguishes this from sibling tools like approve_spend and chp_content_hash.

    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 the tool: to evaluate a proposed action against the CHP Profile B spend gate before approval. However, it does not explicitly mention alternatives, exclusions, or how this tool relates to approve_spend, chp_content_hash, or chp_version, so the guidance is not fully explicit.

    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?

    There are no annotations, so the description carries the full burden of behavioral disclosure. It provides meaningful detail: the exact algorithm (SHA-256), the canonicalization method (float-aware, CHP §3.1), and cross-implementation compatibility. It does not explicitly state the output format (e.g., hex string) or error behavior, but as a pure hashing function this is a minor gap.

    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 is front-loaded with the core hashing algorithm and immediately provides the canonicalization details. Every phrase adds value, and there is no wasted or redundant text.

    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 is simple with one parameter and no output schema, so the description is nearly complete. It conveys the essential purpose, algorithm, and compatibility. The only gap is the lack of an explicit return type, but 'SHA-256' and 'digests' strongly imply a standard hash string, making this acceptable for the tool's low 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?

    The schema covers the single parameter 'value' with a clear description ('JSON-serializable value to hash'), giving 100% coverage. The description adds further meaning by explaining that the value is processed via float-aware canonical JSON, which is additional semantic detail 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 computing a SHA-256 hash over canonical JSON, specifying the canonicalization approach ('float-aware canonical JSON') and protocol reference (CHP §3.1). While it lacks an explicit action verb like 'compute' or 'return', the meaning is unambiguous and distinguishes it from the sibling tools, which relate to spend gating and versioning.

    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 used for hashing JSON objects according to a specific protocol, and mentions compatibility with Python digests. However, it does not explicitly state when to prefer this tool over alternatives, nor does it provide exclusions or prerequisites. The usage context is implied rather than explicitly stated.

    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 carry the full burden. While 'report' implies a read-only operation, it does not explicitly state that it has no side effects, nor does it mention any prerequisites or limitations. It adds minimal behavioral detail beyond the purpose.

    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, front-loaded sentence that states the action and target precisely. There is zero redundancy, and every word contributes to meaning.

    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?

    For a parameterless, output-schemaless version reporting tool, the description is fully sufficient. It captures the entire scope of the tool without unnecessary elaboration, and the lack of structured data means no additional context is required.

    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 baseline is 4. The description correctly avoids parameter explanation, and the schema already covers the empty parameter list. No further semantics needed.

    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 'report' and the specific resources (MCP server and CHP Profile B protocol versions). It distinguishes from sibling tools like spend gate approval or content hashing, making its 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 Guidelines3/5

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

    The description implies usage for retrieving version information but provides no explicit guidance on when to use it versus alternatives. There are no exclusions or alternative tool references, so it sits at 'implied usage' level.

    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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