sigmodx-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct operation: reliability state, input hashing, three decision logging types (anomaly, GL, invoice), and attestation verification. No functional overlap exists.
Naming Consistency5/5
All tools follow a consistent 'sigmodx_verb_noun' pattern (e.g., get_reliability, hash_inputs, log_anomaly_decision). Naming is uniform and predictable.
Tool Count5/5
With 6 tools, the set is well-scoped for a specialized MCP server focusing on Sigmodx operations. Each tool serves a clear purpose without being too few or too many.
Completeness4/5
The tool surface covers core operations: reliability checking, input hashing, decision logging for three key domains, and attestation verification. Minor gaps like a general decision retrieval tool are absent but not critical for the stated purpose.
Average 3.8/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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 carries full behavioral transparency burden. It discloses auto-blocking for segregation violations, which is useful. However, it does not mention side effects, permissions, idempotency, or whether it's a write operation beyond logging. Adequate but not thorough.
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-loaded with the core purpose and usage. Every sentence adds value without redundancy, achieving maximum conciseness.
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?
Given no output schema, complex parameters (8 properties, nested object), and no annotations, the description is insufficient. It does not explain return values, tool effects, or parameter relationships, leaving the agent with an incomplete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description provides no explanation of the 8 parameters, including required fields like 'inputs' and 'rationale'. It does not compensate for the lack of schema descriptions, leaving parameter semantics entirely undocumented.
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 logs a GL entry review decision and lists specific actions (approves, flags, blocks). It distinguishes from sibling tools by explicitly mentioning 'GL entry review' and 'journal entry', which sets it apart from anomaly or invoice decision tools.
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 'Use when an AI agent approves, flags, or blocks a journal entry,' providing clear usage context. It also notes auto-blocking for segregation of duties violations, but does not mention when not to use or compare directly to sibling tools.
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?
Adds behavioral context about automatic escalation for critical severity, which is not in annotations (none provided). However, misses other behavioral traits like idempotency, auth requirements, or side effects. Moderate disclosure.
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?
Two sentences, front-loaded with purpose. No wasted words, but could include brief parameter guidance without bloating. Efficient overall.
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 9 parameters (including nested 'inputs'), no output schema, and no annotations, this description is insufficient. Missing explanation of key parameters, expected input format, and return behavior. Leaves significant gaps for correct invocation.
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?
With 0% schema description coverage, the description should compensate but only mentions the decision_type actions (flag, clear, escalate) implicitly. Does not explain other parameters like 'inputs', 'rationale', or enum values. Minimal added value over schema.
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?
Clearly states the verb 'log', resource 'anomaly detection decision', and context 'financial transaction'. Differentiates from siblings by specifying anomaly-specific actions (flag, clear, escalate).
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?
Explicitly states when to use: 'when an AI agent flags, clears, or escalates a financial transaction anomaly.' Provides behavioral note about automatic escalation for critical severity, but lacks explicit when-not-to-use or alternatives.
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 carries full burden. It discloses a key behavior (client-side hashing for data privacy), but omits details like side effects, required permissions, success/failure responses, or persistence guarantees.
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, both essential: the first states purpose, the second adds an important behavioral constraint. No unnecessary words.
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 logging tool with 6 parameters and no output schema, the description covers purpose, usage, and a key behavioral trait. It is mostly complete, but lacks information on what happens after logging (e.g., attestation confirmation or errors).
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 each parameter has a clear schema description. The tool description adds no additional per-parameter context beyond the schema, so baseline 3 is appropriate.
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's purpose: logging invoice approval decisions for cryptographic attestation, with specific decision types. It distinguishes itself from sibling tools by focusing on invoices, though not explicitly contrasting with other log tools.
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?
Provides explicit guidance on when to use the tool (when an AI agent approves, rejects, or escalates an invoice). However, it does not specify when not to use it or mention alternatives among sibling tools.
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 provided, so description must cover behavior. It mentions no authentication and confirms hash integrity, but does not specify whether it is read-only or has side effects, rate limits, or error conditions. Acceptable for a simple verification but could be more thorough.
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: first states purpose, second provides key detail. Efficient and front-loaded.
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?
Describes purpose, return type, authentication requirement. For a one-parameter tool without output schema, this is nearly complete. However, missing details on error responses or record format, so not a 5.
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?
Verification_string is the only parameter, fully described in schema. Description provides an example, adding marginal value. With 100% coverage, baseline 3 is appropriate.
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?
Clearly states the action 'verify' and resource 'Sigmodx attestation' using a verification string, and mentions returning the record. Distinguishable from sibling tools like logging or reliability checks.
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?
No explicit guidance on when to use vs alternatives. Only mentions 'No authentication required' which is a minor usage hint. Could be improved by contrasting with other verification or reliability tools.
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?
With no annotations, the description carries full burden. It implies a read-only operation via 'Get' and lists possible return values, which adds behavioral context. However, it does not explicitly state side-effect freedom or prerequisites.
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?
Single sentence of 11 words, front-loading the action and result. No redundant or filler content.
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?
Simple tool with 1 parameter and no output schema; description specifies the output states. Minor gap: doesn't explicitly state the return type (string) or error conditions, but overall sufficient for the simplicity.
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 0%, and the description merely references 'a specific scenario' without elaborating on the enum values or their meaning. 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'Get' and resource 'current reliability state' with explicit possible values (ALLOW/LIMIT/BLOCK) and scope (for an agent in a specific scenario). Distinguishes well from sibling tools which handle logging, hashing, and verification.
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?
Implies usage when needing reliability state, but no explicit guidance on when to use vs alternatives (e.g., logging tools might also be contextually relevant). No when-not or exclusion mentioned.
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?
No annotations are provided, so the description carries the full burden. It discloses the deterministic SHA-256 method and the critical privacy trait that the payload is never sent. This is concise but informative for a simple hashing 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?
Two sentences with zero waste, front-loading the action and method. Every sentence contributes useful information.
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 explains input and process but does not mention the output format or return value, which is a gap since no output schema exists. For a hashing tool, the agent needs to know what the tool returns.
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 already covers the required parameter 'payload' with 100% description coverage, so the description adds no new info beyond stating what is hashed. Baseline 3 is appropriate.
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 hashes an input payload using SHA-256, emphasizing the payload is never sent to Sigmodx. It distinguishes itself from sibling tools which focus on reliability, logging decisions, and attestation verification.
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 does not provide explicit guidance on when to use this tool versus alternatives. Usage is implied as a hashing utility, but no exclusions or context for choosing it over other tools are given.
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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