agentrava

by lukisimi

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools have clearly distinct roles: profile, feed, recap, leaderboard, and athlete naming are all unambiguous. The only real boundary issue is log_activity versus snapshot, which both log sessions and return cards, though snapshot's explicit preference for Claude Code work helps clarify the split.
Naming Consistency3/5
The set mixes verb_noun names like log_activity, set_athlete, get_profile, and list_activities with bare nouns like snapshot, recap, and leaderboard, so there is no consistent pattern. All names are readable and lowercase, but the convention is not uniform enough to be considered mostly consistent.
Tool Count5/5
Seven tools is well-scoped for a niche gamified activity tracker, and each tool covers a distinct part of logging, viewing, summarizing, and comparing activities. No tool feels redundant, and the count is appropriate for the server's purpose.
Completeness4/5
The core lifecycle is covered: log_activity and snapshot create activities, list_activities reads the feed, and profile, recap, and leaderboard provide aggregation and comparison. Minor gaps like no delete or update activity endpoint and no single-activity detail view are workable but not severe.
Average 3.6/5 across 7 of 7 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 18 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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of explaining behavior. It says the tool returns recent logged sessions and headline stats, but does not state whether this is read-only, how results are ordered, whether pagination exists, or how the athlete parameter affects results.
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 concise sentence and is front-loaded with the main purpose. It avoids bloat, though it may be too terse to compensate for missing paramdetails.
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?
There is no output schema, no annotations, and one parameter is undocumented. The description conveys only a high-level view of the result and does not mention filtering, ordering, or what 'headline stats' concretely includes. For a simple two-parameter read tool it is close but still has important gaps.
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?
The schema documents limit ('How many, newest first. Default 10.') but athlete is left undescribed in both schema and description. The description adds no parameter meaning, so the agent has insufficient info to correctly use the athlete parameter.
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 this tool returns 'recent logged sessions with their headline stats,' which identifies the resource and output focus. It is not a tautology and can be distinguished from siblings like log_activity, but it does not explicitly contrast with them.
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?
There is no guidance about when to prefer this tool over siblings such as leaderboard or recap, and no mention of alternatives or exclusions. The intended use is only inferred from 'recent' and 'feed,' so the agent does not receive explicit selection criteria.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the ranking behavior but omits important details such as whether the call is read-only, the sorting direction, default limit behavior, or the shape of the returned leaderboard. This is insufficient for an unannotated 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?
The description is a single sentence that front-loads the core action and resource and lists the metric options without any filler. It is efficient and easy to scan.
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 annotations and no output schema, the description is not complete enough for confident invocation. An agent is left without information about the return value format, default parameters, or how the ranking is ordered. The description covers only the basic function.
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?
The description lists the metric enum values, but these are already fully captured in the schema. It adds no explanation of what 'effort' means, and it says nothing about the 'limit' parameter. With 0% schema description coverage, the description fails to compensate for the missing parameter semantics.
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 uses a specific verb ('Rank'), names the resource ('logged sessions'), and enumerates the valid metrics, making it easy for an agent to understand what the tool does. It clearly distinguishes this from sibling tools like list_activities or recap, which have different 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 its siblings. It does not mention alternatives or scenarios where ranking would be inappropriate; the use case is only implicit in the name and the verb 'Rank'.
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 are present, so the description must carry behavioral weight. It explains the scope ('across every logged activity') and the output categories, which gives some transparency about aggregation behavior. However, it does not clarify default behavior when the optional athlete parameter is omitted, response shape, permissions, or whether anything beyond reading occurs.
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 a single, compact sentence with no filler. It front-loads the main output categories and closes with the important scope qualifier ('across every logged activity'). Every phrase contributes meaning.
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?
For a simple tool with one optional parameter and no output schema, the description names the main content areas but leaves some gaps. The term 'trophy case' is not explained, and the behavior when athlete is omitted is not stated. Overall it is adeuate but not fully self-sufficient.
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 description coverage is 100%, and the schema already explains that athlete filters to one athlete. The tool description adds no detail about how the athlete filter interacts with 'every logged activity,' but because the schema is complete, a baseline of 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 communicates that this tool returns an athlete profile built from career totals, current streak, personal records, and trophy case information. It does not use an explicit verb like 'retrieves' or 'returns,' but the tool name plus the resource content make the purpose clear. It is distinct from raw activity listing, though it doesn't explicitly contrast with sibling tools.
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 is given on when to call this tool versus list_activities, recap, snapshot, or leaderboard. The description implies an aggregate/profile use case, but it never states exclusions, alternatives, or prerequisites such as needing a selected athlete.
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 the burden of behavioral disclosure, and it does reveal the output components and the default date range. However, it does not state whether the tool is read-only, whether it respects a selected athlete, or what happens when no data exists.
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 a single sentence with no wasted words, front-loaded with the core purpose and followed by concrete output details. It is appropriately sized for the tool's complexity.
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 is reasonably complete for a non-mutating summary tool, listing the main content of the output card and the default scope. However, with no output schema and no annotations, it leaves the athlete parameter's role ambiguous and does not clarify whether 'everything logged' is global or scoped to the current athlete.
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 75%, and the schema already documents to, from, and title defaults. The description's 'Defaults to everything logged' reinforces the date-range semantics but adds no new meaning for the undocumented athlete parameter.
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 a clear purpose: produce a single card summarizing a whole period with totals, a heatmap, an hour-of-day histogram, trophy case, longest streak, and biggest session. This distinguishes it from list_activities and log_activity, though it does not explicitly differentiate it from snapshot.
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 gives no explicit guidance on when to use recap versus sibling tools like snapshot, leaderboard, or list_activities. It mentions a default scope ('Defaults to everything logged'), but this is a parameter behavior rather than usage routing.
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 the transparency burden and does disclose key behavior: the output is an image card, metrics are mapped gamification-style, and honesty is required. It implies persistence through 'your own history' but does not explicitly state that an activity record is saved.
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?
Three sentences, front-loaded with the tool's purpose and output, followed by the trigger condition. The playful wording earns its place by reinforcing the Strava-style behavior without adding fluff.
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 output is described as an image card, schema documentation covers parameters, and trigger conditions are clear. It could be more complete by explicitly stating that the activity is persisted and what happens on return, but none of this is critical for selecting or invoking the tool.
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 description coverage is 100%, so the schema already documents all 17 parameters. The description adds a helpful metaphor—line churn becomes distance, errors become elevation—but does not explain individual parameter details, which is acceptable given full schema coverage.
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?
States a specific action and result: finish a coding session and receive a Strava-style achievement card as an image. It distinguishes itself by promising the card, badges, and personal records, though it does not explicitly contrast with sibling 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?
Gives clear call triggers: when the user asks to brag or at the end of a session worth remembering. It does not list excluded scenarios or alternative sibling tools, but the guidance is sufficiently clear for an agent to know when to invoke it.
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 the behavioral burden and does well: it discloses that the change applies to past cards too, and warns against guessing. It could add more about overwriting behavior or lack of reversibility, but the core behavioral implications are covered.
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?
Three sentences, each earning its place: the main effect, the athlete/gear distinction, and a necessary user-interaction safeguard. Information is front-loaded and there is no fluff.
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 simple one-parameter setter, the description covers what is set, the scope of the change, and how to obtain the value. It does not describe the return value or error behavior, but that is a minor gap for this mutating tool with no output schema.
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 fully documents the single parameter including format and max length, so the baseline is 3. The description adds useful context about the name being shown on cards, but does not add new parameter-level meaning beyond the 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?
States a specific action ('Set') on a specific resource (the athlete name shown on every card), and clarifies that the athlete is the account owner, not the model/gear. This distinguishes it clearly from siblings like get_profile and list_activities.
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?
Gives explicit usage guidance: always ask the user for the name and never guess from email or filesystem. It does not explicitly name alternatives, but the guidance is clear enough for an agent to know when and how to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden and does so thoroughly: numbers come from the transcript rather than the agent, repeated calls update rather than duplicate, and session guessing has a defined fallback with a named choice.
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?
Every sentence earns its place: core action first, then sourcing, then alternative preference, then idempotency, then default behavior. It is dense but not padded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with optional parameters and no output schema, the description covers the essential call-time decisions: when to use it, what it measures, repeat-safety, and default session selection. Nothing critical is left for the agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema by explaining the no-argument session-guessing behavior and warning the agent to check which session was chosen before repeating numbers.
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?
Opens with a specific verb and resource: 'Log the session that is running right now and return its card.' It also explicitly distances itself from log_activity, making the tool's scope and identity unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives a concrete selection rule: prefer this over log_activity when the work happened in Claude Code. It also clarifies when it is safe to call repeatedly and how the no-argument default behaves.
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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