AgentNave
Server Quality Checklist
Latest release: v0.3.0
- Disambiguation5/5
Each tool targets a distinct lifecycle phase: starting, observing, or stopping an invocation. wait_agent and cancel_agent are clearly differentiated by whether the caller wants to continue observing or actively terminate the work.
Naming Consistency5/5All three names follow the same verb_agent convention with clear verbs: start, wait, cancel. There are no mixed naming styles or vague identifiers.
Tool Count5/5Three tools is a well-scoped count for a focused agent lifecycle server. Each tool fulfills a necessary operation without redundancy or bloat.
Completeness5/5The lifecycle is complete: start an agent, wait for its progress or final result, and cancel when needed. wait_agent also returns final results, so there is no dead-end after an invocation completes.
Average 4.5/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 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
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses important behavior beyond annotations: the call returns immediately without waiting, and the launched provider may read, write, or run commands in cwd subject to native permission controls. This adds meaningful safety and async semantics that annotations alone do not convey.
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: the core behavior is stated first, follow-up observation guidance is second, and the side-effect caveat is third. Every sentence contributes necessary information without 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?
The description covers the essential invocation flow and side-effect profile, and the output schema plus 100% parameter descriptions complete the picture. It does not mention the cancel_agent sibling or explicitly state that the returned ID works with it, but that is inferable from sibling context and not a critical gap.
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%, so the schema already documents all parameters, including cwd, prompt, provider, session_id, timeout_seconds, and provider_options. The description does not add further parameter-level meaning, but it does not need to because the schema carries the full load.
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 specific action: start one subagent and return an in-memory invocation ID without waiting. It also names wait_agent, directly distinguishing this tool from siblings. The title reinforces the resource and action.
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 clear usage context by stating that wait_agent should be used with the returned ID to observe the invocation. It does not explicitly mention cancellation or when not to use this tool, but the asynchronous-start versus observe/cancel relationship is evident.
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?
Annotations already declare destructiveHint=true and idempotentHint=true, so the safety profile is covered. The description adds value beyond those flags by disclosing the already-terminal case — calling cancel on a finished invocation returns its terminal result rather than failing — which explains the idempotency semantics. This aligns cleanly with the annotations, so no contradiction.
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 with zero waste. The core action and return behavior are front-loaded in sentence one, and the routing guidance in sentence two earns its place by preventing misuse of a destructive operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with full annotation coverage and an output schema present, the description covers the action, the return behavior, and the when/when-not decision. The only absent details (exact result shape) are already handled by the output schema, so nothing an agent needs to invoke this correctly is missing.
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%: the single required parameter invocation_id is documented as 'Invocation ID returned by start_agent,' which tells the agent where the value comes from. The description references 'one invocation' consistently but adds no syntax or format detail beyond the schema, so the baseline for high coverage applies.
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 a specific verb and resource — 'Stop one invocation' — and specifies the return behavior ('return its final cancelled or already-terminal result'). It also names the sibling it is not (wait_agent), so an agent can distinguish cancel from the observe-only tool without opening either schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence is explicit: 'Use this only when the Manager intends to stop active provider work' gives the exact triggering condition. It then names the alternative ('use wait_agent to observe work without stopping it'), leaving no ambiguity about when to pick each sibling.
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?
Annotations already mark this as readOnly, idempotent, and non-destructive. The description adds stateful behavior beyond annotations: a running response leaves the invocation active and that wait_agent may be called multiple times. It also clarifies that cancellation is handled by a separate sibling, not by this tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short paragraphs, with the core purpose in the first sentence and operational guidance in the second paragraph. Every sentence adds information; no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the key operational distinction (running vs. final result) and what to do in each case, plus the explicit pointer to cancel_agent. With an output schema present, it doesn't need to detail the return structure, and the timeout semantics are reasonably implied by the running-snapshot outcome.
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%, so the baseline is 3. The description does not add any parameter-level meaning beyond the schema, but the schema already documents invocation_id and wait_timeout_seconds clearly, including defaults and bounds.
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?
States a clear verb-resource pairing ('Wait briefly for one invocation') and the expected outcome ('return either a running snapshot or its final result'). It distinguishes itself from cancel_agent by explicitly naming the cancellation path, and from start_agent by position (waiting follows starting).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on how to respond to a running result: 'call wait_agent again later.' It also delineates the boundary with cancel_agent: 'Use cancel_agent only when the invocation should be stopped.' This is sufficient for an agent to decide between polling and cancelling.
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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