mcp-deadmansnitch
Server Quality Checklist
Latest release: v1.0.1
- Disambiguation5/5
There is only one tool, so there is no possibility of confusing separate tools. The actions within the tool (list, get, create, etc.) are distinct and clearly named, eliminating any ambiguity.
Naming Consistency5/5The single tool name 'snitch' is a noun representing the resource, and all actions follow a consistent verb style (list, get, create, update, delete, pause, unpause). The naming pattern is uniform and predictable, making it easy to understand the available operations.
Tool Count4/5While the tool count is only 1, it effectively acts as a subcommand interface covering all core operations. This is slightly unusual but remains well-scoped given the narrow domain of Dead Man's Snitch monitoring, so the count is reasonable.
Completeness5/5The actions provide full CRUD coverage plus monitoring-specific operations (pause, unpause, check_in) and tag management. No obvious gaps exist for the stated purpose, and the optional parameters cover additional needs like alert types and notes.
Average 4.1/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of disclosing side effects and operational traits. It mentions actions like 'delete', 'pause', and 'update' but does not state whether delete is irreversible, whether pause stops all monitoring, or what side effects check_in has. For a tool with several state-changing and potentially destructive actions, this is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured as a compact action list with consistent formatting: 'action - description. Required/Optional: params'. The opening line establishes the tool's scope, and every subsequent line provides necessary operational detail without filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 10 actions and 11 parameters, the description covers the essential operational aspects: actions, required/optional parameters, and valid enum-like values. An output schema exists, so return-value documentation is not needed. Minor gaps remain, such as the format for 'until' or the exact content of 'alert_email', but these are partially covered by the schema's type declarations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description compensates thoroughly. It maps each action to its required/optional parameters, distinguishes between the singular 'tag' and plural 'tags', and lists valid values for interval (15_minute, hourly, etc.) and alert_type (basic, smart) that the schema does not constrain. This directly adds meaning beyond the raw property types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Manage Dead Man's Snitch monitors,' clearly specifying the domain and resource. It then enumerates all ten actions (list, get, create, update, delete, pause, unpause, check_in, add_tags, remove_tag), making the tool's purpose unambiguous even though the name 'snitch' is cryptic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Each action is paired with required and optional parameters, e.g., 'create - Create snitch. Required: name, interval' and 'list - List snitches. Optional: tags (filter)'. This effectively tells the agent which action variant to use based on available parameters. There are no sibling tools to compare against, so it cannot name alternatives; a 5 would require explicit when/when-not exclusions.
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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