pkgtruth
Server Quality Checklist
Latest release: v0.1.1
- Disambiguation5/5
The two tools are clearly distinguished by cardinality: check_package handles a single package while check_dependencies handles multiple. The usage guidance in each description reinforces when to call which, leaving no real ambiguity.
Naming Consistency5/5Both tool names follow the exact verb_noun pattern with a shared check_ prefix. This is perfectly consistent and predictable.
Tool Count3/5Two tools is on the low end of the typical range, but the narrow domain (npm package verification) justifies a small surface. Still, it feels slightly thin for a server that could reasonably expose more granular operations.
Completeness5/5The tool set fully covers the stated purpose of verifying packages before install: single-package checks and bulk dependency validation. It also bundles multiple critical checks (existence, slopsquatting, install-time scripts, deprecation, abandonment) into each call, so there are no obvious dead ends.
Average 4.2/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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?
With no annotations provided, the description carries the full disclosure burden and handles it well: it states that the call returns existence and flags specific risk patterns (slopsquatting, install-time scripts, deprecation, abandonment), which implies a read-only verification behavior. It does not disclose network behavior or error handling for invalid package names, but those are minor gaps for a verification tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loading the purpose with an imperative verb and the resource immediately. The second sentence's list of risk flags is compact and useful, and the parenthetical on slopsquatting justifies the niche term. Nothing is redundant, though the list of flags makes it slightly long.
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?
For a simple one-parameter tool with no output schema and no annotations, the description covers what the tool does, what it returns, and when to call it. The absence of an output schema makes the described return values particularly valuable. Edge-case behavior (e.g., result shape for a nonexistent package or network errors) is not addressed, but this is a minor omission for a single-package check.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: the single parameter 'name' is already documented with format and examples ('express' or '@scope/pkg'). The description does not add meaning beyond what the schema provides, so the baseline score of 3 is appropriate. It correctly reinforces the singular scope, but adds no new parameter semantics.
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 states a specific verb ('Verify'), a specific resource ('a single npm package'), and the context ('before installing, importing, or recommending it'). It implicitly distinguishes from its plural sibling check_packages by emphasizing 'single', and it enumerates exactly what the check returns: existence, slopsquatting, install-time scripts, deprecation, and abandonment. This leaves no ambiguity about what the tool does.
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?
The description gives an explicit trigger: 'Call this whenever you are about to introduce a dependency you have not verified in this session.' This is clear when-to-use guidance. However, it does not explicitly state when not to use it or name the alternative (e.g., a batch-check sibling), though the singular/plural naming and the verb make the boundary reasonably obvious.
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 provided, the description carries the behavioral disclosure burden. It adds meaningful behavior by stating that results are sorted worst-first, ensuring hallucinated or dangerous packages surface at the top. It does not describe the response format or side effects, but 'verify' strongly implies a non-mutating operation.
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 compact and front-loaded: it states the core action first, then practical use cases, then the key behavioral nuance about sorting. Every sentence earns its place with no 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?
For a simple one-parameter tool with no output schema, the description provides enough context to invoke it correctly: when to use it, what it accepts, and what results look like. It could be more complete by naming check_package as the single-package alternative or describing the result payload, but these are minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the 'names' parameter well. The description reinforces the batch aspect and ties it to dependency-list checks, but it does not add substantially new parameter-level detail beyond what the schema provides.
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 uses a specific verb ('Verify') with a clear resource ('many npm packages at once'), which immediately conveys the tool's batch nature. This distinguishes it from the sibling check_package, which presumably handles a single package.
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?
The description explicitly states when to use the tool: before writing a package.json, running an install command, or handing a dependency list to a user. It does not explicitly mention the alternative for single-package checks, but the batch-focused phrasing provides clear contextual guidance.
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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