figure_library_apply_adopt_versioningApply a cached plan to adopt scientific figure template versions, using an operation ID to prevent duplicate applications and expected digests to reject stale-state updates.
Apply the exact cached plan with operation-id idempotency and stale-state checks.
| Name | Required | Description | Default |
|---|---|---|---|
| planDigest | Yes | ||
| operationId | Yes | ||
| expectedTemplateId | Yes | ||
| expectedSeriesDigest | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are present (readOnlyHint: false, idempotentHint: true), and the description's mention of 'operation-id idempotency' consistently reinforces the idempotentHint, while 'stale-state checks' adds some behavioral detail beyond the annotations. However, the description stays surface-level and does not disclose consequences of stale state or expected outcomes. No contradiction with annotations.
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?
The description is a single, tightly worded 13-word sentence that is front-loaded with the core action. It is highly efficient, though perhaps slightly too terse—a few extra words about prerequisites (e.g., 'run plan_adopt_versioning first') would improve value without sacrificing concision.
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?
Given this is a mutation tool with no output schema and no parameter descriptions, the description is under-specified. It does not explain what happens on success, what the response looks like, what triggers a stale-state failure, or how this 'apply' pairs with its plan counterpart. An agent would struggle to know the postconditions or how to handle results.
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?
With 0% schema description coverage, the description must carry the semantic weight. It partially does: 'operation-id idempotency' clarifies operationId's role, and 'stale-state checks' hints at the expected* parameters' function as concurrency guards. Yet the mapping to individual parameters is indirect and requires significant inference; it does not explicitly enumerate or clarify each field.
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 description uses a specific verb and resource ('Apply the exact cached plan'), clearly indicating that this tool applies a previously created plan. However, it does not explain what 'adopt versioning' accomplishes or differentiate itself from the many other 'apply_*' siblings, leaving some ambiguity about the broader operational purpose.
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?
Usage context is implied rather than explicit. Phrases like 'exact cached plan' suggest a plan must be created first, and 'operation-id idempotency' implies retries are safe. However, there is no explicit when-to-use guidance, exclusions, or mention of alternatives (e.g., 'use after plan_adopt_versioning').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.