CompleteMCP

Server Quality Checklist

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Latest release: v2.0.0
Disambiguation5/5
Each tool has a distinct, non-overlapping purpose. For example, get_jd handles JD input, list_jds lists saved JDs, and get_base_resume vs set_base_resume are clearly separate for reading vs writing the base resume.
Naming Consistency5/5
All tools use a consistent verb_noun snake_case pattern (e.g., get_jd, set_base_resume, validate_resume). Minor plural/singular variations (list_jds vs get_skill) do not detract from overall predictability.
Tool Count5/5
11 tools cover the core resume tailoring workflow without unnecessary extras. The count is well-scoped for the domain, offering enough granularity without being overwhelming.
Completeness4/5
The tool surface covers the full pipeline from JD acquisition to DOCX generation, with validation and listing. However, a tool to retrieve the content of a saved tailored resume is missing, which may force file-level access.
Average 4/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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 carries full burden for behavioral disclosure. It only states that the tool lists files with titles and filter status, but does not mention any behavioral traits such as pagination, ordering, or whether it returns user-specific data.
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, clear sentence that is front-loaded with the action. No extraneous words; every part earns its place.
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 the tool has no parameters, no output schema, and no annotations, the description is minimally adequate. However, it lacks explanation of what 'filter status' means or whether any filtering is implied. Some additional context would improve completeness.
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 input schema has zero parameters, so according to rules the baseline is 4. The description adds value by indicating that the output includes 'titles and filter status', providing context beyond the empty schema.
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 'List' and the resource 'saved job description files', and specifies the included attributes ('titles and filter status'). It effectively distinguishes from siblings like 'get_jd' (single JD retrieval) and 'list_resumes' (different resource type).
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, such as 'get_jd' for a specific JD or 'list_resumes' for resumes. There is no mention of context, prerequisites, 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 provided, so description must disclose behavior; it only mentions listing files but omits return format, pagination, ordering, or whether JSON and DOCX are listed together.
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, clear sentence with no wasted words; front-loaded with the key action and resource.
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?
Adequate for a simple list tool with no parameters, but lacks details on output structure (e.g., file IDs, names) that would help an agent parse results.
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 has zero parameters and 100% coverage, so baseline is 3; description adds value by specifying file types (tailored JSONs and built DOCXs), raising score to 4.
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 verb 'List', resource 'generated resume files', and specifies the subtypes 'tailored JSONs and built DOCXs', distinguishing it from siblings that get/save individual resumes.
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 vs. other list tools (list_skills, list_jds) or when not to use it.
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 the file path behavior (default vs custom), but lacks details on overwriting, permissions, or error handling. With no annotations, the description partially covers behavioral 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?
Single sentence with front-loaded action, no wasted words. Efficiently conveys core information.
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 write operation with three parameters and no output schema, the description provides sufficient context about the file location. No output schema exists, so return value details are not expected.
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?
All three parameters are described in the schema (100% coverage). The description adds value by explaining the default path for output_path and the filename slug usage, enhancing understanding beyond schema.
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 action 'save', the resource 'tailored resume JSON', and the default write location. It is a specific verb+resource that distinguishes from sibling tools like get_tailoring_rules or build_docx.
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. It does not mention prerequisites like requiring a tailored resume first, or that it should be used before build_docx.
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. It discloses that the tool overwrites the base resume and affects validation, but lacks detail on permissions, error states, or consequences for existing tailored resumes. This is 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no fluff. Every word adds value: specifies action, input format, and behavioral consequence. Front-loaded and concise.
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 a simple single-parameter tool with no output schema or annotations, the description adequately covers purpose, input, and effect. However, it could mention the return value (e.g., success or error) or any required preconditions for completeness.
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 single parameter resume_json is described similarly in both schema and description ('Full base resume JSON as a string'). The description adds the context that it must be the full resume, not partial, which provides some extra meaning beyond the schema's description.
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 'Replace' the 'bundled base resume' with a new one, and specifies that it becomes the new source of truth for validation. This distinguishes it from siblings like get_base_resume (retrieval) or save_tailored_resume (saving tailored versions).
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 usage when you want to update the base resume and notes its role in validation, but does not explicitly state when not to use it (e.g., for viewing or partial updates) or mention alternatives like get_base_resume for retrieval.
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 checks performed (identity, fabrication count, etc.) but does not describe the output format, error behavior, or whether the tool is read-only. 'Validate' suggests a safe operation, but more detail would improve 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 a single sentence that efficiently conveys the purpose and key checks. It is front-loaded with the verb and resource, with no wasted words.
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 a simple tool with one parameter and no output schema, the description adequately explains what the tool does but omits the return value (e.g., success/failure, list of issues). This gap in behavioral completeness lowers the score from a potential 4.
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 covers 'json_path' as 'Path to tailored JSON file' (100% coverage), meeting the baseline of 3. The description adds value by clarifying that the file is a 'tailored resume JSON' and that validation is against the 'base resume', providing context beyond the schema.
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 action ('validate'), the object ('tailored resume JSON'), and specifies what it checks ('identity, fabrication count max 10, bullet count guardrails, hedging phrases'). It distinguishes itself from sibling tools like 'save_tailored_resume' or 'get_base_resume' by focusing on validation.
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 validation should occur after tailoring a resume, but it does not explicitly state when to use this tool versus alternatives like 'get_tailoring_rules' or 'save_tailored_resume'. No exclusions or when-not-to-use guidance is 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?
Describes output format (bundled file with summary), but no annotations exist. Lacks disclosure on side effects, permissions, or whether it's read-only. Some value added beyond raw schema.
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 clear action and result. Front-loaded with key purpose, 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 zero-parameter retrieval tool. Describes what is returned and adds context about the summary. Could note static vs. dynamic nature, but not essential.
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?
No parameters; baseline 4 applies. Description adds value by explaining the output structure (job summary with bullet counts), though no parameter semantics to clarify.
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 the tool returns the base_resume.json file with a job summary showing bullet counts. Distinct from siblings like 'get_jd' and 'set_base_resume'.
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?
Implied usage as source of truth, but no explicit guidance on when to use vs. alternatives like 'get_skill' or 'list_resumes'. No when-not scenarios.
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 provided; description adds some behavioral detail (output filename derived from base resume Contact.Name) but lacks disclosure of side effects like file overwriting or dependency on base resume. Adequate but not thorough.
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 states core function, second adds prerequisite and behavior. No redundant words, front-loaded with essential information.
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 2 params and no output schema, the description covers purpose, prerequisite, and output naming. Could mention error handling or file system impact, but overall sufficient for this tool's role in the workflow.
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% with clear descriptions for both parameters. The description adds extra context: output_path is optional and auto-derived, and filename derives from Contact.Name in the base resume, enhancing schema info.
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 builds a DOCX resume from a tailored JSON file, specifying the input and output. Distinguishes from siblings by mentioning prerequisite validate_resume and unique file generation behavior.
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?
Explicitly states the prerequisite: 'Should only be called after validate_resume passes.' This provides clear usage context, though it doesn't discuss alternatives or when not to use.
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 that the tool returns content, slug, and output paths, and that it can save files (via save_path). However, it doesn't clarify if saving is automatic or optional, or describe any side effects beyond returning data.
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 sentence states purpose and return values. Second states constraints and optional parameter. Every word adds value, no fluff.
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 5 parameters, no required fields, and no output schema, the description provides good context: how to invoke (exclusive choice), what it returns, and optional save behavior. It could briefly mention what the output paths look like or the file format, but it is mostly complete.
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 description coverage is 100%, providing basic parameter info. The description adds meaningful constraints: 'exactly one of url, text, or file_path' (not in schema) and gives an example for slug ('CompanyName_Role'), which enhances usability beyond the schema 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 the tool's purpose: 'Get a job description from a URL, pasted text, or a file. Returns JD content, slug, and output paths.' It uses a specific verb ('get') and resource ('job description'), and distinguishes itself from sibling tools that list JDs or handle resumes.
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 'Provide exactly one of: url, text, or file_path,' which is a clear constraint. It also mentions optional slug. However, it doesn't provide guidance on when to use this tool versus alternatives like list_jds or get_skill.
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 must disclose behavior. It indicates a read operation ('Returns'), but does not mention any side effects, authentication needs, or whether the rules are static or dynamic. For a simple zero-param tool, this is adequate but not thorough.
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, each adding value: first defines purpose, second gives usage guidance. No filler 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?
For a parameterless read tool with no output schema, the description provides essential purpose and usage advice. It could mention the type or format of rules (e.g., string list), but the current description is sufficient for an agent to decide when to invoke it.
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 input schema has zero parameters with 100% coverage (none to cover). The description adds no parameter info because there are none, which is appropriate. Baseline for 0 params is 4.
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 'Returns' and the resource 'resume tailoring rules', distinguishing it from sibling tools like get_jd or get_base_resume. It also adds a usage hint about reading before creating tailored resumes.
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 instruction 'Read these before creating any tailored resume' explicitly tells when to use this tool (preparation step). It does not mention when not to use it or alternatives, but the context is clear.
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 provided; the description indicates a read operation ('Return') but offers no additional behavioral details (e.g., idempotency, authentication requirements). Adequate for a simple retrieval but lacks depth.
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, front-loaded with the primary purpose. No redundant words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one required parameter and no output schema, the description fully covers what the agent needs: what it does, how to get the input, and that it returns the content. No missing context.
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% with an example. The description reinforces the parameter usage by saying 'Use the exact name from list_skills' and repeats the example, adding value beyond the schema.
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 action ('Return') and the resource ('full SKILL.md content for one bundled skill'), with a specific scope ('bundled skill') that distinguishes it from sibling tools like list_skills.
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?
Provides explicit guidance to use the exact name from list_skills and gives an example, helping the agent know when and how to invoke the tool. Does not explicitly exclude other scenarios but is sufficient.
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?
The description implies a safe read operation ('list') with no side effects. While no annotations exist, the description does not explicitly state read-only behavior or lack of side effects, but it is clear enough. It could be improved by noting it returns all skills or any pagination, but for a simple list it is adequate.
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 succinct sentences efficiently convey purpose, usage, and relation to sibling tools. No unnecessary words, and key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description is complete. It explains what the tool returns, when to use it, and how it fits with other tools (get_skill). No gaps remain.
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?
With zero parameters, the baseline is 4. The description adds no parameter-level detail, which is fine since none exist. It correctly focuses on output semantics instead.
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 lists bundled resume/JD tailoring skills with short descriptions. It distinguishes itself from get_skill (full content) and other listing tools like list_jds and list_resumes. The verb 'list' is specific and the resource is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance on when to use: before tailoring a resume, especially to read 'fabricators'. Also recommends get_skill for full content, providing a clear alternative and workflow 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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