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pamela-0

boot-doctor-mcp

by pamela-0
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools serve completely different purposes: diagnose_symptoms walks through a troubleshooting decision tree, while lookup_beep_code is a reference lookup. There's zero overlap or ambiguity about which to call in any scenario.

    Naming Consistency5/5

    Both tools follow the identical imperative verb_noun snake_case convention (diagnose_symptoms, lookup_beep_code). Perfect consistency, even if the sample size is small.

    Tool Count3/5

    Two tools is on the thin side for a general-purpose troubleshooting server, but the scope here is deliberately narrow (diagnosis guidance + beep-code reference). It works, but feels minimal.

    Completeness3/5

    The core workflows (symptom-based guidance and beep-code lookup) are covered, but natural additions like a debug-LED/literal code reference, or a POST-code table, would round out the domain. Notable but not critical gaps.

  • Average 4.4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 3 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

  • 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 that the tool outputs a ranked sequence based on cost/speed, not a definitive diagnosis. It also explains the semantic difference between 'fans spin briefly then stop' as a PSU/motherboard signal, adding useful behavioral context. It does not mention side effects, but the tool is likely read-only and non-destructive, which is not stated but also not contradicted.

    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 front-loaded with the main purpose in the first sentence, then provides parameter details in a readable, line-separated format. It is longer than ideal, but the length is justified by the need to explain 7 parameters. No redundant sentences; each piece adds value.

    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 has an output schema (not shown) so it needn't describe return values. Given the complexity (7 params, 1 required), the description covers the input semantics and the overall behavior (ranked steps by cost). It lacks an explicit note about when to use the sibling beep-code tool, but that is a minor gap. Overall, the description is sufficient for an agent to effectively invoke the tool.

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

    Parameters5/5

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

    Schema description coverage is 0%, so the description must fully explain parameters. It does exactly that: each of the 7 parameters (powers_on, fans_spin, fans_stay_running, display_output, tried_cmos_reset, tried_minimal_config, tried_different_cable_or_monitor) is given a clear, meaningful explanation that goes beyond the schema titles. For example, it explains the difference between fans spinning and staying running, and what 'tried minimal config' means. This is exemplary compensation for 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?

    The description clearly states the tool's purpose: providing 'ranked next troubleshooting steps' for a PC that won't boot. It distinguishes itself from a diagnosis and from the sibling tool (lookup_beep_code) by focusing on a general sequence rather than beep codes. The verb 'diagnose' is accurate, and the resource (PC boot/display issues) is explicit.

    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 implies when to use it: when a PC won't boot or show display, and what input is needed (what's been tried). It notes it's not a diagnosis, setting expectations, but does not explicitly state when to use the sibling tool (e.g., when beep codes are present). The context is clear enough for an agent to infer the appropriate scenario.

    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?

    Discloses that it returns None when no match is found, explains the difference between BIOS types, and notes that modern boards may not have a speaker. Since no annotations are provided, the description carries the transparency burden and does so effectively.

    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 detailed yet efficient, with a clear structure: purpose, parameter constraints, pattern examples, and return behavior. It avoids unnecessary fluff while covering all essential 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 that an output schema exists (though not shown), the description does not need to detail return values, but it still mentions the None case, which is useful. It also covers edge cases like modern boards without speakers, making the context complete enough for correct usage.

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

    Parameters5/5

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

    The schema has 0% coverage for parameter descriptions, but the description fully explains both parameters: pattern is free text with examples, and bios_type is constrained to three valid values. This fully compensates for the lack of 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 tool looks up beep patterns against real BIOS beep-code tables. It specifies the resource (beep-code tables) and the action (lookup), and distinguishes itself from the sibling tool diagnose_symptoms by focusing on beep-code lookup.

    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 required inputs (bios_type must be one of the listed values, pattern format with examples) and warns about potential pitfalls (different tables for different BIOS types). It does not explicitly contrast with the sibling tool, but the usage is clear enough.

    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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