aspark-graph

by a-lottes

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Server Quality Checklist

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Latest release: v0.4.0
Disambiguation5/5
Each tool targets a distinct operation: building the graph, querying nodes by various criteria (single node, substring, neighbors, path), impact analysis, health reporting, and staleness check. No two tools serve the same purpose.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with lowercase and underscores (e.g., build_graph, find_nodes, gate_health). The naming is predictable and uniform.
Tool Count5/5
With 9 tools, the server is well-scoped for a graph-based repository analysis tool. Each tool provides a clear and necessary function without overloading or underproviding capabilities.
Completeness4/5
The set covers core graph operations (build, query, traverse) and domain-specific features (impact, story trace, health). Minor gaps exist, such as lacking a tool to list all graph nodes or delete the graph, but these do not hinder primary workflows.
Average 2.8/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 37 commits in the last 12 weeks
- Last stable release on July 28, 2026
- 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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. The description only describes the output format but does not disclose behavior like read-only nature, algorithm, or requirements (e.g., graph must already be built).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The one-sentence description is too short and vague, lacking substantive content. It does not balance brevity with informativeness.
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 the complexity of a shortest path tool, with no output schema and no annotations, the description is insufficient. It fails to explain return format, error cases, or integration with sibling tools.
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?
With 0% schema description coverage, the description should add meaning to parameters. It hints at 'two nodes' but does not explain a, b, or repo, leaving their semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description mentions 'ordered path' and 'no path' result, vaguely indicating graph path finding, but does not specify 'shortest' or the context (e.g., code repository graph). It fails to differentiate from sibling tools like get_neighbors or story_trace.
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 on when to use this tool versus alternatives such as build_graph or get_neighbors. No prerequisites or exclusions are stated.
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 present, so the description must disclose behavioral traits. It fails to mention case sensitivity, whether the substring match is exact or fuzzy, pagination, or potential performance impact. For a read-only search, it does not confirm immutability.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, but it omits essential details that would benefit the agent. It is not verbose but is under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and sparse description, the tool lacks critical context such as return format, error handling, or result limits. For a search operation, this is insufficient for confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description does not explain any parameters. The meaning of 'repo' (likely repository path) and 'type' (scope of nodes) is left ambiguous, forcing the agent to guess or assume defaults.
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 the action (find) and resource (nodes), and specifies matching on id or name substring with optional type filter. This distinguishes it from sibling tools like get_node (single node) or get_neighbors (adjacent nodes).
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 provided on when to use this tool versus alternatives such as get_node or search. The description only states what it does without context or exclusions.
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 bears full responsibility for disclosing behavioral traits. It does not state if the tool is read-only, destructive, requires authentication, or has side effects. 'As data' implies read-only, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it front-loads jargon ('aSPARK gate invariants') without explanation. While not verbose, the structure could be improved by clarifying the tool's action earlier.
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 the lack of output schema, annotations, and parameter explanations, the description is incomplete. It does not explain the return format, how to interpret the data (orphan tasks, etc.), or how the tool fits into the broader set of sibling tools.
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?
With 0% schema description coverage, the description must explain parameters, but it only mentions 'feature' generically. It does not clarify what 'feature' means, what 'repo' (default '.') refers to, or how they affect the output. The parameter semantics are almost entirely absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description vaguely indicates that the tool retrieves data about gate invariants (orphan tasks, unverified acceptance criteria, open findings) for a feature, but lacks a clear verb like 'get' or 'list', making its purpose ambiguous. Compared to sibling tools, it's not immediately obvious what specific action it performs.
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 alternatives like 'impact', 'staleness', or 'story_trace'. There is no mention of prerequisites, context, or scenarios where gate_health is appropriate.
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?
The description is minimal and does not disclose important behavioral details such as performance characteristics, ordering of results, pagination, or treatment of edge types. Annotations are absent, so the description carries full burden but fails to provide sufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one line), which is efficient but comes at the cost of completeness. It front-loads the purpose but omits essential details, making it borderline under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, four parameters with zero descriptions, and sibling tools that suggest complex graph operations, the description is severely incomplete. It fails to explain the return format, the meaning of 'edge_types' and 'repo', or how depth works, leaving the agent with significant ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain any of the four parameters beyond the mention of 'depth'. With 0% schema description coverage, the description should compensate, but it offers no meaning for 'id', 'repo', or 'edge_types'. The agent cannot infer parameter semantics from this description alone.
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 clearly states it returns nodes within 'depth' hops in both directions, using the intuitive phrase 'what touches this?'. This effectively conveys the core functionality and distinguishes it from siblings like 'shortest_path' (which finds paths) or 'build_graph' (which constructs full graph).
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 provided on when to use this tool versus alternatives like 'shortest_path' or 'find_nodes'. There is no mention of when not to use it, prerequisites, or context where it might be inappropriate.
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?
With no annotations, description carries full burden. It only states the function but does not disclose side effects, auth needs, or any behavioral traits beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is very short but includes irrelevant 'US-4' in parentheses. It is efficient but could be cleaner without the extra noise.
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 one optional parameter and no output schema, the description should at least hint at the return type (e.g., boolean). It does not, leaving the agent guessing about output format.
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?
Schema coverage is 0% for the 'repo' parameter. Description adds no explanation about the parameter's meaning or usage, leaving the agent without clarity.
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?
Description clearly states the tool reports whether the built graph matches the repo on disk. Verb 'report' and resource 'staleness' are specific, and it distinguishes from sibling tools like build_graph and find_nodes.
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 on when to use this tool vs alternatives. No exclusions or context provided.
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 present, so description must convey behavior. It discloses the output structure (acceptance criteria, tasks, code links) but does not mention read-only nature, side effects, or performance characteristics. Adequate but not comprehensive.
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?
Single sentence, front-loaded with the main action. Efficient but could benefit from breaking out the components for clarity.
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?
Without an output schema, the description partially describes the return value (QA verdict, tasks, code links). However, it omits how parameters like 'repo' and 'feature' influence results, and whether multiple stories are returned. Adequate but has 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?
Schema description coverage is 0%, but the description fails to clarify the roles of 'repo', 'story', and 'feature'. It only mentions 'user story' implicitly. This leaves the agent without understanding how each parameter affects the result.
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 it retrieves a 'full thread of a user story' including acceptance criteria with QA verdict, plan tasks, and code links. It provides a specific verb ('trace' implied) and resource, and is distinct from sibling tools like build_graph or find_nodes.
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 on when to use this tool or when to prefer alternatives. The description only lists output contents, not context or prerequisites.
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 provided, so the description carries the full burden. It discloses the mutual exclusivity of input parameters and the output format (stories with confidence), but does not cover error handling, performance, or other behavioral traits.
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?
Two concise sentences: first defines purpose and output, second gives usage constraint. No unnecessary words.
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?
Given no output schema or annotations, the description adequately defines input, output, and a key usage rule. It lacks details on error conditions or return structure confidence interpretation, but is likely sufficient for an AI agent.
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 0%, but the description adds meaning for 'files' (list of files) and 'diff' (git diff range) and the 'not both' constraint. However, the 'repo' parameter is not explained, which is a minor gap.
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 clearly states it computes the blast radius of a change, listing stories and acceptance criteria depending on files or a diff range, each tagged with confidence. It is specific and distinguishes from sibling graph tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies the input constraint (pass either files or diff, not both) but does not explicitly compare to alternative tools like build_graph or find_nodes, leaving the agent to infer usage context.
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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