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MohitDabas

SigmaLineage MCP

by MohitDabas
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Python
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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: one focuses on rare event baselines, another on Sigma hunts, and the third on Sigma hunts with lineage tracing. There is no overlap or ambiguity.

    Naming Consistency3/5

    The first tool uses a noun phrase pattern (rare_events_baseline), while the other two use a verb-noun pattern (run_sigma, run_sigma_lineage). This inconsistency in naming style may cause confusion for an agent.

    Tool Count4/5

    With 3 tools, the set is slightly small but well-scoped for the domain. Each tool serves a clear function without unnecessary bloat, fitting within the typical 3-15 range.

    Completeness4/5

    The tools cover the core workflows: baseline analysis, sigma hunts, and lineage tracing. There are minor gaps (e.g., no tool for managing rules or results), but the surface is complete for intended use.

  • Average 2.6/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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

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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

  • Behavior2/5

    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. It mentions running a hunt and lineage tracing, and returning results, but does not disclose side effects like file writes to output_dir, required permissions, or whether it modifies input data. The read-only or destructive nature is unclear.

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

    Conciseness3/5

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

    The description is a single sentence, which is concise but at the cost of clarity. It front-loads the core action but omits necessary details. It is not verbose, but brevity reduces utility.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness1/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given 6 parameters (4 required) and a complex workflow (hunt + lineage), the description is severely incomplete. It does not explain prerequisites, output format (despite having an output schema), or typical use cases. The description fails to provide a minimal operational context for the agent.

    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?

    With 0% schema description coverage, the description adds no meaning to parameters. It mentions evtx_path, sigma_rules_path, mapping_path, and output_dir implicitly, but does not define them, their formats, or relationships. Parameters 'levels' and 'skip_hunt' are completely ignored, offering no guidance on usage.

    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 it runs a Sigma hunt with lineage tracing, returning paths/summary. It implies a combination of hunt and lineage steps, distinguishing it from 'run_sigma' sibling which likely does only the hunt. However, it could be more explicit about what 'process_lineage paths/summary' entails.

    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?

    No guidance on when to use this tool versus siblings. Sibling 'run_sigma' suggests a simpler hunt-only option, but the description does not explain the trade-offs (e.g., when lineage is needed). No when-not or alternative context provided.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    With no annotations provided, the description must disclose behavioral traits. However, it only mentions reading CSV data and returning results, without stating whether the tool is read-only, what happens on errors, or any side effects. The agent cannot assess safety or side effects.

    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 sentence, concise and to the point. However, it sacrifices necessary detail for brevity. It could be more informative without becoming wordy.

    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?

    Despite having an output schema, the description does not explain what 'rare tuple events' are, how baseline frequencies are computed, or the output structure. The tool has 4 parameters and an output schema, yet the description omits crucial context.

    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%, so the description must explain parameters. It hints at CSV paths but does not describe max_results, max_baseline_count, or their defaults. The agent cannot deduce the meaning of these parameters from the description alone.

    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 states the tool returns rare tuple events with baseline frequencies from parsed CSV data. This is a specific verb-resource combination, but it does not differentiate from sibling tools run_sigma and run_sigma_lineage, which likely have overlapping purposes.

    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 provides no guidance on when to use this tool versus alternatives, nor does it specify prerequisites or context. The agent is left without criteria for selection.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    With no annotations, the description must disclose behavioral traits. It only mentions returning a summary, but does not explain side effects (e.g., creating output files, deleting anything, required permissions). No mention of whether it modifies input files or requires network access.

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

    Conciseness3/5

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

    The description is concise (one sentence) but at the expense of necessary detail. It is not verbose, but the minimalism leaves gaps that reduce its overall utility.

    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 four required string parameters, a tool name implying a security workflow, and the existence of an output schema (though not detailed), the description is insufficient. It does not explain the workflow, prerequisites, or what the output contains, leaving the agent underinformed.

    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 description coverage is 0%, so the description must explain parameters. It does not describe any of the four parameters (evtx_path, sigma_rules_path, mapping_path, output_dir) beyond their names, providing no added meaning for an AI agent.

    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 runs a Chainsaw Sigma hunt and returns a summary, using a specific verb ('Run') and resource ('Chainsaw Sigma hunt'). It distinguishes itself from siblings like 'rare_events_baseline' and 'run_sigma_lineage' by focusing on a general Sigma hunt, implying a different scope or output.

    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 provides no guidance on when to use this tool over alternatives, no prerequisites, no exclusions. It simply states what it does without context about when it's appropriate, leaving the agent to guess.

    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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