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log_rpe_marks

Write the athlete's EFFORT MARKS on a completed activity: RPE 1-10 at a moment of the session ("the second rep was a 7, not a 9", "I tapped 9 by mistake on the test, it was a 6"). Each mark: t = seconds into the session on the MOVING clock (the clock of get_activity's blocks and effort_marks), v = RPE, step = what it was ("Threshold 2/4", optional). get_activity returns the current marks as effort_marks. Pass the WHOLE corrected set with replace:true to change or remove a mark; without replace the marks are added. The athlete can also add, drag and edit them themselves in the activity card's RPE tab. Not the session RPE (that is log_session_rpe) and not the fatigue test's answers (log_sft_answers). Saves on return.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marksYes
replaceNo
activity_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only declare the write/no-open-world profile; the description goes well beyond them by disclosing that replace:true must carry the WHOLE corrected set to change or remove a mark, that otherwise marks are appended, that the athlete can edit the same marks in the RPE tab, and that changes persist ('Saves on return'). Minor tension with destructiveHint=false exists since replace can remove a mark, but the removal is small and reversible, not truly destructive.

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?

Front-loaded with the core action, and every clause carries information (clock semantics, replace rule, sibling disambiguation, persistence). It is dense and runs long with several parenthetical quotes, which costs a little readability, but nothing is wasted.

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 mutation tool with no output schema and no annotations beyond the safety profile, this covers the necessary ground: input clock conventions, the add-vs-replace choice, sibling routing, and return behavior ('Saves on return'). Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden and does: t is defined as seconds on the MOVING clock (aligned to get_activity's blocks/effort_marks), v is the RPE, step is the context label, and replace's whole-set semantics are spelled out. This is meaning the schema's bare types cannot convey.

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?

Specific verb (Write) plus precise resource (EFFORT MARKS for an activity), and it explicitly distinguishes itself from the two nearest siblings, log_session_rpe and log_sft_answers. An agent can tell exactly what this does without opening the schema.

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?

States when to use it, names the alternatives it is NOT ('Not the session RPE (that is log_session_rpe) and not the fatigue test's answers (log_sft_answers)'), and gives the replace:true vs default add semantics as an explicit decision rule.

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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