mcp-overleaf-server

by abhi-ramtel

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but the presence of both `render_and_compile` (which can produce a cover letter) and a separate `render_cover_letter` creates some ambiguity. Agents may be uncertain which to use for cover letter generation. Otherwise, tools like `batch_plan` and `batch_render` are clearly paired, and the rest are well-separated.
Naming Consistency3/5
The majority of tools follow a verb_noun pattern (e.g., `list_applications`, `render_and_compile`), but there are inconsistencies: `overleaf_sync` reverses the order (noun_verb), and `overleaf_commit_push` uses two verbs. The naming is still readable, but the mixed conventions detract from predictability.
Tool Count5/5
With 11 tools, the server covers the full workflow from CV retrieval to compilation, batch processing, ATS analysis, and application tracking. Each tool earns its place, and the count is well within the ideal 3-15 range for a focused domain.
Completeness4/5
The toolset covers the essential lifecycle: fetching master CV, tailoring, rendering, batch handling, ATS scoring, and tracking applications. Minor gaps exist, such as no tool for directly editing the master CV or deleting tracker entries, but these are peripheral to the core functionality.
Average 3.8/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 17 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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How to sync the server with GitHub?

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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool scores and splits gaps, which implies a read-only analysis. However, it does not mention any side effects, authentication, or rate limits, leaving some behavioral gaps.
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: the first covers purpose and output, the second specifies inputs. Every word adds value with no redundancy or 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?
The description lacks detail on output format (e.g., numerical score, categories). Without an output schema, this is a significant gap. It also does not mention that jobDescription is required or that resumeText and texPath are alternatives, reducing completeness for an 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?
The description clarifies that only one of resumeText or texPath should be provided, adding meaning beyond the schema. The jobDescription parameter is implied but not explicitly explained. With 67% schema coverage, the description compensates adequately but could describe jobDescription semantics.
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 scores resume keyword coverage against a job description and categorizes gaps. The verb 'score' and resource 'resume-job description keyword match' are specific. While it doesn't explicitly contrast with sibling tools, the purpose is distinct enough from related tools like get_master_cv or prepare_tailoring.
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. There is no mention of prerequisites, exclusions, or common use cases, which limits the agent's ability to choose correctly among siblings.
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 provided, the description must fully disclose behavior. It lists the output components but does not specify whether the tool is read-only, requires any permissions, or has side effects. There is no mention of error conditions or the exact format of returned data beyond general names, leaving ambiguity about what the agent should expect.
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 short (two sentences) and front-loads the key output components. However, the first sentence is somewhat meta ('Return everything YOU (the host model) need'), which is slightly indirect but still functional. No extraneous information.
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 5 parameters, no output schema, and no annotations, the description is incomplete. It mentions output components like 'deterministic JD keyword signals' and 'strict anti-fabrication rules' without explaining their structure or how the agent should use them. The reference to 'TailoredContent JSON' is vague, and the agent may need more detail to correctly produce the required output for render_and_compile.
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 5 parameters, but only 40% have descriptions (jobDescription and template). The tool description does not add any additional meaning or usage hints for the parameters like jobUrl, company, or position. It fails to compensate for the low schema coverage, leaving the agent to infer their roles from context.
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 provide the host model with everything needed to tailor a resume/CV to a job description. It specifies the resource ('tailoring brief') and the verb ('return'), and the inclusion of specific components (master CV, JD signals, rules, schema) distinguishes it from siblings like 'get_master_cv' and 'render_and_compile'.
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 tells when to use the tool (to get all necessary information for tailoring) and what to do afterwards (call render_and_compile with TailoredContent JSON). It does not, however, mention when not to use it or provide alternatives for other scenarios, but the instruction to use this before rendering 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, so description must cover behavioral traits. It mentions upsert behavior and file path, but lacks details on side effects, permissions, or idempotency guarantees.
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, no fluff. Front-loaded with action, resource, and key behavior. 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?
Despite 9 parameters and no annotations, the description is minimal. It covers core behavior but lacks details on return value, workflow integration, and parameter explanations.
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 11% (low). The description only adds meaning for company and position (upsert keys), leaving other parameters unexplained. Does not compensate for low 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 tool adds or updates a row in the application tracker CSV file, with upsert behavior on company+position. This distinguishes it from sibling tools like list_applications or get_master_cv.
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?
No explicit guidance on when to use this tool versus alternatives. The note about 'regenerating not duplicating' implies idempotency but doesn't provide context for choice.
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 bears full responsibility. It discloses output file naming and a validation/flagging behavior for unsupported quantitative claims. However, it omits other behavioral traits such as side effects (file creation), error conditions, or resource requirements beyond the master CV.
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 concise at two sentences, leading with the primary purpose and output naming. The second sentence packs content rules and constraints efficiently. However, this density slightly reduces readability; separating rules into a list could improve clarity without adding length.
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 complexity (4 parameters, nested object) and lack of output schema, the description covers file naming, content guardrails, and conversion control. It lacks expected output format or return value details, but the primary purpose is clear and sufficient for an AI agent to use correctly.
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%, so the baseline is 3. The description adds minimal extra meaning beyond the schema: it explains the default output name pattern and rephrases the 'compile' parameter's effect. It does not elaborate on the structure or constraints of nested parameters like 'content.paragraphs' beyond what the schema already provides.
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 uses specific verbs ('compile', 'write', 'save') and a clear resource ('one-page cover letter styled to match the résumé'). It specifies the exact output filename pattern (<Company>_<Position>_CoverLetter.pdf) and scope (one page, drawn from master CV). This clearly distinguishes it from sibling tools like 'render_and_compile' by emphasizing content sourcing rules.
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 provides explicit content guidelines (3-4 paragraphs, no invented data) but does not explain when to prefer this tool over siblings like 'render_and_compile' or 'batch_render'. It lacks when-to-use, when-not-to-use, 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.
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 Overleaf git access is a premium feature, that failure is cached, and that a normal 'unavailable' result is returned instead of an error. However, it does not warn about potential side effects like overwriting local files during pull.
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 two sentences, but the first word 'Optional.' is somewhat ambiguous and could be removed or clarified. Overall, it is fairly concise and front-loaded with the main action.
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 covers the main purpose and behavior regarding availability and caching, but it lacks details on the return value format (e.g., what 'list the .tex files' means in terms of output). Given no output schema, more context would be beneficial.
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%, so both parameters are already described in the schema. The description adds no new information beyond what the schema provides (e.g., 'force' and 'project' descriptions are identical). Baseline 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 action: 'Clone (or pull) your Overleaf project via its git repo and list the .tex files.' It uses a specific verb (sync) and resource (Overleaf project), and distinguishes it from the sibling tool overleaf_commit_push.
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 explains when to use the tool and provides guidance: if the feature is unavailable, it returns an 'unavailable' result (not an error) and the agent should continue with local templates. However, it does not explicitly compare to alternatives like overleaf_commit_push.
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, so description carries the burden. It discloses that push publishes, but lacks details on destructive potential, rollback, or permission requirements.
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, front-loaded with clear action, minimal waste. Every sentence serves a purpose.
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?
With 5 parameters and no output schema or annotations, the description is brief. It omits details on commit flow, error handling, and the project parameter.
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 high (80%), and the description does not add extra meaning beyond the schema descriptions. The 'project' parameter lacks description in both schema and 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 title and description clearly state the tool commits changes and optionally pushes to Overleaf. It distinguishes from siblings like overleaf_sync by focusing on commit and push actions.
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 provides guidance on when to use push ('set push=true only when you intend that'), but does not explicitly mention alternatives or when not to use the tool.
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 side effects (auto-logging to tracker, caching) and the two operational modes, which adds value beyond the schema. However, with no annotations, it lacks details on idempotency, error behavior, and permissions required.
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 focused paragraph that front-loads the main action and includes necessary technical details without excessive verbosity. It could be slightly more concise but is well-structured.
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 covers the core batch behavior and auto-logging but omits mention of optional cover letter support and template options (resume/cv). Given the complex input schema and lack of output schema, more details 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 description explains the conditional logic between 'content' and 'reuseFrom' parameters, clarifying that 'content' is only needed for GENERATE jobs and for others 'reuseFrom' is used to resolve content automatically. This adds significant guidance beyond the schema descriptions.
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 renders, compiles, auto-logs, and caches a batch of jobs in one call. It distinguishes from sibling tools like 'batch_plan' (planning) and 'render_and_compile' (per-job) by emphasizing no per-job round trip and referencing the batch plan.
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 that this tool should be used after 'batch_plan' and instead of calling 'render_and_compile' for each job. It explicitly mentions the two modes (GENERATE vs reuse) but does not explicitly state prerequisites or when to avoid using 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?
No annotations provided, so description carries full burden. It discloses the return value (parsed CV with stable IDs) but does not mention side effects, auth requirements, or format details. Since it's a read operation with zero parameters, basic behavior is clear 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?
Single sentence that conveys the entire purpose without any superfluous words. Front-loads the action and key details.
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 zero parameters and no output schema, the description sufficiently explains what the tool returns. Could be improved by specifying the output format or linking to related tools, but is adequate for the simplicity.
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 exist, schema coverage is 100%. Baseline for 0 parameters is 4, and the description adds no parameter information as none is needed.
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 a parsed master CV (cv.md) with stable IDs for tailoring. The verb 'Return' is specific, and the resource and scope are precisely defined, distinguishing it from sibling tools like prepare_tailoring or render_and_compile.
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 usage before tailoring by mentioning 'stable ids used for tailoring', but no explicit when-to-use or alternatives are given. Sibling tools exist but no guidance on selection.
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 the full burden of behavioral disclosure. It correctly indicates a read operation ('return') but omits details like potential performance impact, whether the data is fresh, or if authentication is needed. The simplicity of a no-parameter list-all makes this acceptable.
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 nine words, front-loaded with the core action, and contains no wasted content. It is highly efficient for its purpose.
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, the description effectively states what it returns. However, it could briefly mention the expected row structure or field names, especially since no output schema is provided. Still, it is largely 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?
There are no parameters, and the input schema is empty. The description does not need to add parameter details. The baseline for 0 parameters is 4, and the description meets it without requiring additional explanation.
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 all rows from the application tracker sheet, matching the verb 'list' and specifying the data source. It distinguishes from siblings like 'update_tracker' and 'ats_report' by focusing on a full read-only list.
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 for retrieving the complete list of tracked applications, but does not explicitly state when to use it over alternatives or provide any exclusions. For a simple read tool, this is adequate but not exemplary.
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 bears full burden. It discloses clustering, caching, and shared reasoning behavior, but does not mention the output format, side effects, or permissions needed. The agent would benefit from knowing what the tool returns and whether it is purely 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with no redundant information. It front-loads the main purpose and function, then provides actionable steps for usage. Every sentence adds value.
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 covers purpose, usage order, clustering logic, caching, and hints at output (which jobs need content). It is missing explicit output structure and error/edge case handling, but is otherwise complete for a planning tool.
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 67% (jobs parameter lacks description). The description compensates by explaining that jobs are clustered by keyword similarity and that roles share reasoning passes, adding meaning beyond the schema. The other parameters (useCache, threshold) are already described in 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 tool's purpose: planning up to 10 jobs by clustering similar roles and checking a cache, then indicating which jobs need fresh content. It distinguishes itself from siblings like 'batch_render' by specifying that this tool is for planning before writing content.
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 instructs to call this tool before writing content for multi-job requests, and mentions that after planning one should call 'batch_render'. It implies it is for multiple jobs but does not explicitly exclude single-job scenarios or mention alternatives like 'prepare_tailoring'.
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 are provided, so the description carries the full burden of behavioral disclosure. It discloses key behaviors: content injection, anti-fabrication verification, PDF compilation, file naming, auto-logging, and return of provenance warnings and ATS coverage report when applicable. It does not mention potential side effects like overwriting files, but the action is clear enough for safe invocation.
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 five sentences, each serving a distinct purpose: main action, cover letter guidance, auto-logging note, and return description. It is front-loaded with the core purpose, with no wasted words. Ideal balance of completeness and brevity.
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 complexity (14 parameters, nested content object, no output schema), the description covers the main purpose, key behavioral nuances, and return values. It mentions provenance warnings and ATS coverage report, which are critical for understanding tool output. It could be slightly more complete by noting prerequisites (e.g., requires a tailored content from previous step), but overall it is sufficiently informative.
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 79% schema description coverage, the schema already documents most parameters. The description adds behavioral context for parameters like coverLetter (recommended, generates matching letter) and jobDescription (triggers ATS report), which enhances understanding beyond the schema. The description does not repeat what the schema already covers, adding value in parameter semantics.
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 specifies the tool's function: inject TailoredContent into LaTeX, verify bullet traceability, compile to PDF, and save with a specific naming convention. It also distinguishes itself by mentioning companion cover letter generation, which is a key differentiator from sibling tools like render_cover_letter.
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 instructs to 'ALWAYS pass `coverLetter` too unless the user opted out', providing strong guidance on when to use the cover letter feature. It also states the application is auto-logged, but lacks explicit comparison with sibling tools like batch_render for when to use this single-render tool versus batch alternatives.
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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