apply_tag_suggestions

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

With no annotations, the description carries the full behavioral burden, and it does disclose the two most important facts: this is a WRITE OPERATION and it requires the tag write scope. It stops short of the remaining high-value disclosures — whether persistence appends to or replaces existing tags, whether it is idempotent, and whether it fails on duplicate tags.

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?

Two short sentences with the operation stated first and the critical constraint (write scope) second — well front-loaded with no filler. It is efficiently sized, though the second sentence is a fragment bolted on rather than integrated prose.

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?

The presence of an output schema means return values need not be described, so the gap lies elsewhere: required-parameter semantics and the effect of re-applying tags are both missing for a mutation tool. Adequate but with clear gaps for a write operation with zero annotation coverage.

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% across all three required parameters. The description only vaguely maps 'tags' and the entity ('experiment or item'), leaving 'id' entirely unexplained and giving no hint about the accepted values for 'entity_type' (which has no enum). With three undocumented required parameters, the description fails to compensate for the coverage gap.

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?

States a specific verb ('Persist') and resource ('tags to an eLabFTW experiment or item'), which clearly separates it from the read-only suggest_tags sibling by virtue of the write semantics. The parenthetical '(suggested)' hints at the workflow relationship but the description never names suggest_tags directly, so sibling differentiation is implied rather than explicit.

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?

The phrase 'a list of (suggested) tags' implies this is the persistence step following suggest_tags, so the intended usage context is weakly conveyed. However, there is no explicit when-to-use statement, no statement of what happens if tags already exist, and no stated alternative for a non-persisting path.

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