Update ai tracking schedule

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

Annotations already mark this as a non-read-only, non-destructive, non-open-world mutation. The description adds genuinely non-obvious context beyond that: immutable revisions must be preserved, explicit budget consent is required, retry keys stay stable, and — importantly — it explicitly does not launch a paid baseline. That negative side-effect disclosure is exactly the kind of signal annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences keep it tight, but the leading sentence is vague filler that doesn't front-load the actual operation, and the constraint list reads as terse fragments. It is compact without being wasteful, yet the ordering puts the least informative statement first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter mutation with a deeply nested required configuration object and no output schema, the description is thin. It never clarifies update semantics (full replacement vs. partial), how the reviewed configuration/revision fields should be sourced, or what a caller should expect on success. The consent and paid-baseline notes help, but substantial complexity is left to the schema alone.

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

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

Schema description coverage is 100%, so the schema already documents all 9 parameters including the nested configuration, consent, and revision fields. The description references consent and revisions obliquely but adds no syntax, format, or usage detail beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The stated purpose is the vague 'Manage project-scoped AI tracking', which restates the general domain rather than specifying that this updates an existing schedule's configuration. It does not distinguish itself from siblings like create_ai_tracking_schedule or archive_ai_tracking_schedule. A rough sense of the resource exists but the specific verb+resource pairing is blurry.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance and no mention of alternatives (create_ai_tracking_schedule, preview_ai_tracking_run, archive_ai_tracking_schedule all sit nearby). The clause 'does not start an automatic paid baseline' hints at a boundary but frames it as behavior, not as routing advice. An agent gets no help deciding when this tool is the right call.

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