mindgap

by grburgess

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clear, distinct purpose with no overlap. For example, add_node handles single upsert, ingest handles batch writes, link and unlink are opposites, find and get_node serve different retrieval needs, and context provides a digest rendering.
Naming Consistency4/5
All tools share the 'mindgap_' prefix and use clear verbs, but some are verb_noun (add_node, get_node, remove_node) while others are single verbs (context, export, find, ingest, link, stats, unlink), representing a minor inconsistency.
Tool Count5/5
With 10 tools, the set is well-scoped for a graph knowledge base server, covering core operations without being overly large or insufficient. Each tool serves a necessary function.
Completeness4/5
The tools cover CRUD-like operations via upsert, batch ingest, retrieval, search, linking, unlinking, stats, export, and context rendering. Minor gaps include lack of explicit update tool (handled by upsert) and dedicated tag management, but core workflows are well-supported.
Average 3.5/5 across 10 of 10 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 43 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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}
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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 mentions 'upsert' (implies insert or update), return values (persisted row, stubs_created, warnings), and a default for confidence. Missing details on idempotency, conflict behavior, permissions, or destructive potential.
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?
Two concise sentences with no wasted words. Front-loaded with the core action. However, could be slightly more structured to include parameter hints.
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 9 parameters, no schema descriptions, and no output schema, the description is incomplete. Lacks explanation of upsert semantics, meaning of 'stubs_created', and details on 'replace' behavior. Significant gaps for proper tool usage.
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%, so description must compensate. Only the 'confidence' parameter is explained as defaulting to 0.7. Other key parameters like 'replace', 'id', 'type', 'tags', 'urls' are not described, leaving the agent uninformed.
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 'Single node upsert', which is a specific verb+resource combination. It distinguishes from sibling tools like mindgap_get_node (read) and mindgap_remove_node (delete). However, 'upsert' is jargon and might not be universally understood.
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 mindgap_ingest or mindgap_get_node. No exclusions or prerequisites mentioned.
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?
The description declares 'Read-only', which is a key behavioral trait. However, with no annotations provided, it should disclose more (e.g., whether it modifies state, what side effects exist). It adds the fact that it mirrors 'mindgap context', but lacks details on output format or performance.
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 of 15 words, highly concise and front-loaded with the action 'Render a markdown digest'. No unnecessary information is present.
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 tool has two parameters and no output schema, the description omits explanation of the 'depth' parameter, does not specify the return format beyond 'markdown', and lacks differentiation from similar query tools (e.g., mindgap_find). More context on neighbor links and expected output is needed.
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 input schema has two parameters (query, depth) with 0% description coverage. The description only mentions 'for a query', partially explaining the 'query' parameter, but omits depth entirely. It fails to add meaning beyond the schema field names.
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 tool 'renders a markdown digest (matched nodes + neighbor links) for a query', which is a specific verb+resource. It distinguishes from siblings like 'add_node' or 'export' by focusing on query-based digest, though it could be more explicit about difference from 'mindgap_find'.
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 mentions 'Read-only' implying safe usage, but provides no guidance on when to use this tool versus alternatives like 'mindgap_find' or 'mindgap_get_node'. No exclusions or alternative suggestions are given.
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, the description must disclose behavioral traits. It only lists output fields but does not state whether the tool is read-only, requires authentication, or has side effects. Key behavioral information is missing.
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 concise sentence that immediately conveys the tool's purpose. Every word earns its place with no redundancy.
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 parameterless tool with no output schema, the description provides the core output fields but lacks details on scope (e.g., which graph), limitations, or response format. It is minimally adequate but could be more descriptive.
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?
The tool has zero parameters, and the input schema has 100% description coverage (empty). Per guidelines, baseline is 4. The description adds no parameter info, which is acceptable since none exist.
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 indicates the tool returns graph counts including nodes, edges, and breakdowns by type and relationship. While the verb is implied, the resource ('graph') and output types are explicit, distinguishing it from sibling tools that modify or search the 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 mindgap_find or mindgap_context. The description lacks context about prerequisites, typical use cases, or exclusions.
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 must disclose behavior. It mentions returns results + count and limit range, but lacks details on search behavior (e.g., exact vs fuzzy, case sensitivity, or what fields returned). No contradictions.
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?
One sentence, very concise and front-loaded with purpose. Could add more detail without being verbose, but acceptable for brevity.
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?
No output schema, no annotations, and only 0% parameter coverage. Description omits return format details (just 'results'), and doesn't clarify search behavior. Incomplete for effective use.
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%, so description should explain each parameter. It mentions 'query/type/tag' and limit with bounds, but does not define what query, type, or tag mean. The limit is well-documented, but the others are unclear.
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 searches nodes by query, type, and tag, and returns results with a count. This distinguishes it from sibling tools that add, get, remove, or link nodes.
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?
It implies use for searching/finding nodes, but does not explicitly state when to use this versus alternatives like mindgap_get_node or mindgap_stats. No when-not or alternative tool guidance.
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 must fully disclose behavioral traits. It mentions the default output path and that absolute paths are allowed, but does not specify whether the operation is destructive, requires permissions, or if it captures all data types. The behavior beyond file naming is opaque.
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 two concise sentences with no filler. The first sentence states the core function, and the second adds key parameter detail. Every word earns its place.
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 the tool's simplicity (one optional parameter, no output schema, no annotations), the description covers the essential: what it does and the parameter behavior. It does not explain return values or confirm comprehensiveness of the snapshot, but for an export tool, it is largely sufficient.
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?
The schema has one optional parameter 'out' with no description. The tool description adds meaning by stating the default path pattern and that an absolute path is allowed. With 0% schema coverage, the description compensates well, though it could be more precise about the parameter format.
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 explicitly states 'Write a JSON snapshot of the whole graph', which is a specific verb ('write') and resource ('JSON snapshot of the whole graph'). This clearly distinguishes it from sibling tools like 'mindgap_add_node' or 'mindgap_ingest'.
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 lacks any guidance on when to use this tool versus alternatives. It does not suggest when not to use it or compare to other tools like 'mindgap_get_node' or 'mindgap_stats'. The usage context is only implied.
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 the description carries full burden. It discloses the hard-fail (isError) behavior on missing endpoints and confirms no auto-stubbing. This is good transparency for the core mutation, though no side effects or permissions mentioned.
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 two sentences, economical and front-loaded. Every word earns its place – no fluff or repetition.
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?
With 5 parameters and no output schema, the description is incomplete. It explains the error condition but ignores parameter semantics, return value, and potential side effects. The agent cannot reliably invoke the tool without guessing parameter meanings.
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 description adds no parameter documentation. The 5 parameters (created_by, src, dst, rel, weight) are entirely unexplained, leaving the agent without guidance on their meaning or format.
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 the tool adds an edge between two existing nodes, with a specific verb 'Add' and resource 'edge'. It explicitly says 'EXISTING' to differentiate from node creation, and contrasts with sibling tools like mindgap_add_node and mindgap_unlink.
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?
The description implies when to use: when linking existing nodes, and not when endpoints might be missing (since it hard-fails). It does not explicitly list alternatives or when-not-to-use, but the hard-fail behavior is a strong guideline.
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, description carries full burden; it discloses cascading of edges and destructiveness, enough for a simple delete tool, but omits auth needs or reversibility.
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 short sentences, front-loaded with essential info, no wasted 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?
Adequate for a low-complexity tool with one param and no output schema; covers core action and side effect, though return value or error details are missing.
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 has 0% description coverage for the single 'id' parameter; description adds no meaning beyond the parameter name.
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?
Clearly states 'Delete a node (cascades its edges)' with specific verb and resource, and distinguishes from siblings that add or link nodes.
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?
Implies use for stub cleanup and labels it destructive, but lacks explicit when-to-use vs alternatives like mindgap_unlink for edge removal or mindgap_get_node for inspection.
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?
Discloses the destructive action (delete), the return value (removed count and orphaned nodes), and side effects. However, with no annotations, it could further clarify permanence or permissions needed.
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?
Single sentence with no wasted words; all essential information is front-loaded.
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 3-param tool with no output schema, the description covers the action, parameters, and return info well. Could be improved by mentioning when to use this vs. siblings.
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 description explains that src and dst are endpoints and rel is optional, adding some meaning beyond the schema param names. But it does not provide data types, format, or examples, and schema coverage is 0%.
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 the verb (Delete) and resource (edge(s)) between src and dst, and distinguishes from siblings like mindgap_link (which adds edges) and mindgap_remove_node (which removes 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 versus alternatives like mindgap_link or mindgap_remove_node. No context on prerequisites or typical usage scenarios.
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 full burden. It discloses that a missing id returns node:null (clean miss, not an error) and notes the default depth. This is transparent for a simple read operation, though it omits discussion of authentication 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. All information is front-loaded and essential.
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 fetch tool with 2 params and no output schema, the description covers purpose, depth behavior, and missing-id behavior. However, it does not describe the return structure (e.g., node data and neighborhood format), which would be helpful. Still, it is largely complete.
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 0%, so the description must compensate. It adds meaning for 'depth' (range 1..3, default 1) but does not clarify what 'id' represents (e.g., node ID string). The missing-id behavior is about the result, not the parameter meaning. Partial coverage.
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 the verb 'Fetch' and the resource 'a node and its neighborhood'. It specifies the depth range (1..3) with a default of 1, and distinguishes this read operation from siblings like mindgap_add_node or mindgap_remove_node.
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 implies use for fetching a node and its neighbors, but it does not explicitly state when to use this tool versus alternatives like mindgap_find or mindgap_context. No when-not or exclusion criteria are provided.
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?
Discloses key behaviors: atomic validation (rejecting entire payload if any edge endpoint is invalid) and return of persisted rows for verification. No annotations provided, so description fully carries the burden, and it does so well.
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 sentences that are concise and front-loaded with the most important identity ('Validated batch write (workhorse)'). Every sentence adds value without redundancy.
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?
Without an output schema, the description explains the return value (persisted rows) and validation behavior. It covers key aspects for a batch write tool, though more details on parameter constraints would improve completeness.
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 has 0% parameter description coverage. Description only mentions 'nodes' and 'edges' generically, with no details on fields like created_by, id, etc. No compensation for the lack of schema documentation.
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?
Clearly states it performs a validated batch write that upserts nodes and adds edges in one transaction. Distinguished from siblings like mindgap_add_node (single node) and mindgap_link (single edge) by being a batch 'workhorse'.
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?
Implicitly indicates it's the primary tool for batch operations ('workhorse'), but does not explicitly state when to use alternatives or exclude cases. Clear context but lacks direct when-not-to-use 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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