RECLUSE Spider MCP Server

by vinsenzo83

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Latest release: v0.2.0
Disambiguation5/5
Each tool targets a distinct step in the spider verification workflow: planning, classification, checklist, signals collection, pattern recording, and corpus retrieval. There is no overlap in functionality.
Naming Consistency4/5
All tools use the 'spider_' prefix and underscore separators, but some names are verb_noun (e.g., spider_plan, spider_record_pattern) while others are noun-only (e.g., spider_checklist, spider_signals). This minor inconsistency prevents a perfect score.
Tool Count5/5
With 6 tools, the set is well-scoped for a specialized verification server. Each tool earns its place without being redundant or excessive for the domain.
Completeness4/5
The tools cover the core lifecycle: planning, classification, checklists, signal detection, pattern recording, and corpus access. A minor gap could be a dedicated analysis or reporting tool, but the workflow is largely complete.
Average 3.5/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 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
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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 are provided, so the description must disclose behavioral traits. It does not mention side effects, idempotency, rate limits, or authentication needs, leaving significant gaps.
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, well-structured sentence that front-loads the purpose. It is concise without being terse, though it could be more efficient.
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?
No output schema exists, so the description should describe the return structure. It lists components but lacks detail on format or fields, leaving the agent with an incomplete picture.
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 100% with both parameters described. The description adds high-level context (e.g., 'spiders to throw') but does not significantly enhance meaning beyond the schema.
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 returns a verification plan for a target, specifying components like spiders, learning patterns, and principles. It distinguishes itself from siblings by focusing on planning rather than classification or checklist.
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 mentions 'call at round start,' providing timing context, but lacks explicit guidance on when not to use or alternatives among sibling tools.
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 behavior. It mentions adding to a corpus and being checked later, but it does not describe side effects (e.g., overwrite behavior, deduplication), input validation, return values, or error conditions. The description is too minimal for a tool with 6 parameters.
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 extremely concise with two short sentences, no wasted words, and immediately front-loads the action. It earns its place without any fluff.
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 (6 parameters, no output schema, no annotations, multiple siblings), the description lacks important context: it does not mention prerequisites (e.g., an existing corpus), the format or structure of the one-line pattern, what the tool returns, or how it integrates with the sibling tools. It is insufficient for a developer to fully understand usage.
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 100%, with each parameter having a clear Korean description. The tool description adds no additional meaning or context beyond what the schema already provides, so the baseline score of 3 is appropriate.
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's purpose: to distill and add bug patterns caught in the current round to a learning corpus as one-line patterns, to be checked first in the next round. It uses specific verbs and resources, and the restriction 'only actually caught ones' adds clarity.
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 implies when to use (after catching bugs in the round) but provides no guidance on when not to use or how this tool differs from siblings like spider_checklist, spider_signals, or spider_pull_corpus. No explicit alternatives or exclusions are given.
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 full burden. It mentions that the tool reflects cost, privilege escalation, and order integrity path, which adds specific behavioral context. However, it does not clarify if the tool modifies data (though '분류' and '반환' suggest read-only) or provide details on side effects or security implications.
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, front-loaded with the main action, and contains no unnecessary words. Every sentence provides value: purpose, when to use, and behavioral context. Excellent conciseness.
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 gives the core purpose and usage context but lacks details on the return format (model/verification key count) and does not fully explain how parameters like 'severity' influence behavior. Given the absence of output schema and annotations, more completeness would be beneficial.
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 only 50% (only 'area' has a description). The tool description does not add any extra meaning beyond what the schema provides; it does not explain the 'severity' parameter or elaborate on the usage of 'area'. This leaves the undocumented parameter unclear.
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's action: classifying findings into King/Mid/Baby spiders and returning model/verification counts. It also mentions the context of use (before dispatching modified spiders), providing a specific verb and resource. However, it does not explicitly distinguish this from siblings, though the siblings 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool ('수정 거미 급파 전 호출' - call before dispatching modified spiders). It does not provide when-not-to-use or alternatives, but the context is clear and the sibling tools are distinct in function.
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, description provides behavioral context: fallback to built-in checklist when file is missing, and merging with session verification data (privilege escalation, order, cost, events). However, it does not mention side effects, auth requirements, or whether the tool is 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence conveys the tool's purpose and key behavior efficiently, though it is somewhat dense and could benefit from clearer structure or bullet points for readability.
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?
Given no output schema and one optional parameter, the description explains the output nature (checklist with evidence) and fallback logic. However, it does not clarify that the dimension parameter is optional or what happens when omitted, leaving some ambiguity.
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% but description adds enumeration of dimension values (인증/데이터/단위/끊긴고리/권한경계/폴백/런타임/순서/비용/이벤트 등) that are not present in the schema, enhancing parameter understanding.
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 it returns a per-dimension full checklist requiring evidence, and merges built-in checklist with session verification meshes. It is specific about the resource and verb, and distinguishes from sibling tools like spider_plan or spider_classify_tier by focusing on checklist generation.
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 explicit guidance on when to use this tool versus alternatives such as spider_plan or spider_signals. Usage is only implied from the description, with no conditions, prerequisites, or exclusions stated.
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 discloses key behaviors: verified priority, filtering by tag/klass, and graceful fallback to internal corpus. However, with no annotations, it omits details like authentication, rate limits, or response format, which are important for a pull operation.
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 concise, with two sentences that front-load the purpose and then provide additional details. No extraneous words or repetition.
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?
Given 4 parameters, no output schema, and no annotations, the description covers the core functionality but lacks details on return format, pagination, or the nature of the remote corpus, leaving some gaps for a fully autonomous agent.
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 only 50% (tags and verified have descriptions, klass and limit do not). The description does not add any new parameter semantics beyond what is already in the schema, failing to compensate for the undocumented parameters.
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's verb 'pull' and resource 'shared corpus', and specifies filtering by tag/klass and verified priority, distinguishing it from siblings like spider_record_pattern which presumably records patterns.
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?
It specifies a concrete use case: 'for checking known traps at round start'. However, it does not explicitly state when not to use it or provide alternatives, leaving some ambiguity about broader applicability.
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 provided, the description carries full burden for behavioral disclosure. It states the tool returns detection signals and fix principles, implying a read-only operation. However, it does not detail output format, side effects, or prerequisites, limiting transparency.
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 in Korean, tightly packed with purpose and usage guidance. No redundant information; every sentence adds value.
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 tool has 3 optional parameters, no output schema, and no annotations. The description covers what it returns and when to use it, but omits output structure and behavioral details like idempotency or rate limits. Adequate for basic use but not fully 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 description coverage is 67% (tag and klass have descriptions; tier lacks one). The description adds that parameters are filters, which aligns with schema. However, the missing description for tier enum values (king/mid/baby) is a gap that the description does not fill.
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 returns detection signals and fix principles for empirical bug classes, with filtering by klass/tier/tag. It distinguishes from siblings like spider_plan (planning) and spider_pull_corpus (pulling corpus) by emphasizing execution after planning.
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 explicitly says 'after planning, execute these signals as-is to collect evidence,' providing clear context for when to use the tool. It also mentions filtering parameters. However, it does not explicitly exclude use cases or name alternatives among siblings.
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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