read_practice_prompt

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

Annotations already establish readOnlyHint, idempotentHint, and destructiveHint=false. The description adds substantial behavioral detail: exclusions (no original tags/subject/old answers/analysis/feedback), no OCR or erasure, clean_images returns hash-verified net images with a 12MiB cap, and refusal on missing/changed/unverified images with no fallback. This is valuable transparency beyond 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 dense run-on paragraph with multiple clauses separated by commas and semicolons. While every clause conveys information, it is not front-loaded or structured, making it harder to parse quickly. It could be reorganized with bullets or clearer separation.

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 five parameters, no output schema, and a complex set of preconditions, the description covers many edge cases and behavioral rules. However, it omits any explanation of the two required identifiers (record_id, expected_revision) and gives only a hint about the return (record_id/source_revision). An agent would still lack enough to call the tool confidently.

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 0%, so the description carries the full burden. It explains presentation (text vs clean_images) and practice_kind (original vs exercise/variant) to some degree, but never defines the required record_id or expected_revision, nor clarifies exercise_index beyond '变式需下标'. Critical parameters remain unexplained.

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 states a specific action: '练习前只取当前版本题面与中性display_label' (before practice, fetch only the current version question text and neutral display_label). It distinguishes this from fetching original tags, subject, old answers, reference answers, analysis, or feedback. However, it does not explicitly name sibling alternatives like read_element or read_document, so an agent must infer the differentiation.

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?

It gives a clear context ('练习前') and preconditions ('题目须已纳入；变式需下标及答案检查通过，只支持text'), plus a warning not to treat the read tool as proof of independent answer. But it does not explicitly say when to use this versus other read tools or what to do if preconditions fail beyond refusal.

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