arcbounty-mcp
Server Quality Checklist
Latest release: v0.6.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: listing bounties, getting specific bounty details, and retrieving reputation. No overlap or ambiguity.
Naming Consistency5/5All tool names follow the verb_noun pattern with snake_case (list_open_bounties, get_bounty, get_reputation), consistent throughout.
Tool Count3/5With only 3 tools, the surface is thin for a bounty board server, but it may be appropriately scoped for a read-only query interface. Borderline.
Completeness2/5Missing key operations for bounty interaction (apply, submit work, award) and user management. The set covers only querying, not full lifecycle.
Average 3.9/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 98 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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This repository includes a glama.json configuration 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 provided, so description carries full burden. It only states it retrieves reputation, but does not disclose behavioral traits such as authentication requirements, idempotency, or rate limits.
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?
Single sentence, no fluff, front-loaded with key information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should explain return structure more thoroughly. It lists components but not exact format. With no annotations, behavioral completeness is lacking. Adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with a descriptive parameter description. The tool description adds value by clarifying that omitting agentId uses the server's own configured agent, going beyond the schema.
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 clearly states the verb 'Get' and the resource 'ERC-8004 agent's on-chain reputation score', and specifies the returned components (average score, total feedbacks, total jobs). It distinguishes from sibling tools which deal with bounties.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use vs alternatives. Usage is implied but not stated. There are no 'when-not-to-use' or alternative tool mentions.
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 full burden. It reveals that the description is fetched from IPFS, a key behavioral detail. However, it does not disclose other potential traits like auth requirements or side effects (likely read-only).
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 a single focused sentence with no wasted words. It is front-loaded with the core purpose and includes the important IPFS detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (one param, no output schema), the description is adequate but could be more explicit about what 'full details' includes. The IPFS mention adds value, but the agent might benefit from knowing the return structure.
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% and the schema already provides a detailed description of jobId. The description merely repeats 'by jobId' without adding new meaning, so baseline 3 is appropriate.
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 clearly states 'Get full details for one bounty by jobId', with a specific verb and resource. It also adds 'including its description fetched from IPFS', which distinguishes it from sibling tools like list_open_bounties and get_reputation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a jobId and need full details, but no explicit guidance on when to use this vs alternatives. It does not mention that list_open_bounties should be used to find available bounties.
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?
No annotations provided, so description carries full burden. It discloses that only open (unassigned, unresolved, not expired) bounties are listed and that rewards are in USDC. This covers key behavioral aspects for a read-only list tool, though it omits details like pagination or auth requirements.
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?
Two sentences, no wasted words, efficient and scannable. Every element serves a purpose.
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?
With 6 optional parameters, all described in schema, and no output schema, the description provides sufficient context (scope, platform, reward type) for an agent to understand what the tool returns. Sibling tools listed for disambiguation.
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?
Input schema has 100% description coverage, so description adds no extra parameter meaning. Baseline 3 is appropriate; the description's mention of 'open' and 'USDC' is context, not parameter specifics.
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?
Description clearly states 'List open bounties' with specific filtering criteria (unassigned, unresolved, not-yet-expired) and distinguishes from sibling tools (get_bounty vs list, get_reputation). The verb 'list' and resource 'open bounties' are specific.
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?
Description says 'Use this to find work to take on, or to survey the current market.' This gives clear context for when to use the tool, but does not explicitly exclude alternatives like get_bounty for single items or provide negative 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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