Skip to main content
Glama

Export race plan PDF

export_race_plan_pdf

Export a Hi-Fi PDF or standalone checkpoint card from an existing CRSProf artifact. The CRSProf supplies the course/profile/plan data; options are presentation-only overrides such as title, subtitle, metric/imperial unit system, format, and file name. Omit unit_system unless the user explicitly asks for metric or imperial.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
optionsNo
crsprof_artifact_idYesExisting CRSProf artifact ID containing the course/profile/plan data to render.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorsNo
job_idYesCourseProfiler job ID to poll with get_job.
statusYesJob status, e.g. queued, running, succeeded, or failed.
progressNo
warningsNo
created_atNoISO-8601 creation timestamp.
expires_atNoISO-8601 expiration timestamp.
started_atNoISO-8601 start timestamp, when available.
status_urlNoRelative API URL for polling this job.
completed_atNoISO-8601 completion timestamp, when available.
result_artifactsNoArtifacts produced by the job, including role metadata.

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden and does meaningful work: it states the tool renders from an existing CRSProf artifact and that options are 'presentation-only overrides,' indicating a non-mutating export operation. It also gives a concrete behavioral rule to omit unit_system unless explicitly requested. It does not discuss auth or output handling, but the core behavior is disclosed.

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?

Three tightly scoped sentences with no filler: the main action comes first, the data source and option scope are second, and the crucial unit-system instruction is last. Every sentence 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?

For a two-parameter export tool with a nested options object and an output schema, the description covers the essential selection and invocation information: what to export from, what options can change, and the one subtle default behavior. It does not need to describe return values because an output schema exists; minor gaps like default format behavior are covered by the schema.

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 only 50%, so the description must compensate; it does by enumerating the option categories (title, subtitle, units, format, file name) and adding the important unit_system omission rule. This adds meaning beyond the raw schema, though some parameter format details are left to 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 opens with a specific verb and resource: 'Export a Hi-Fi PDF or standalone checkpoint card from an existing CRSProf artifact.' This names the output, the input, and the fact that the artifact already exists, making it easy to distinguish from sibling tools like create_race_plan or get_artifact.

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 establishes a clear precondition (an existing CRSProf artifact) and clarifies that options are presentation-only, so an agent can infer when export is appropriate. However, it never explicitly names alternatives or states when not to use this tool, leaving some selection guidance to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation4/5

Each tool targets a distinct step in the course/race-planning workflow, and descriptions carefully separate concerns like importing, enriching, segmenting, and generating a plan. The main ambiguity is among the multiple get_*_requirements helpers, but their target phases are clear enough to avoid persistent misselection.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (create_, enrich_, export_, generate_, get_, import_, search_, submit_, validate_). There is no mixing of camelCase or inconsistent verb styles, making the API predictable and easy to navigate.

Tool Count4/5

With 16 tools, the server is at the upper edge of the ideal range but each tool serves a distinct purpose in a complex pipeline covering course import, enrichment, segmentation, runner profiling, plan creation, PDF export, validation, and catalog submission. The count feels justified for the domain rather than bloated.

Completeness4/5

The toolset covers the full lifecycle from course discovery/import through enrichment, segmentation, runner profiling, race plan generation, PDF export, and catalog submission. Minor gaps exist, such as lack of artifact list/delete/update tools and no direct race-plan editing, but agents can work around these via get_artifact and get_job.

Resources