research_analyze

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

Goes well beyond the annotations with concrete operational constraints: 180 s timeout, 64 MiB output cap, 512 MiB process heap, no code execution of the target, evidence persistence, and no automatic business conclusions. Annotations (readOnlyHint=false, destructiveHint=false) are consistent with a tool that writes Evidence without destroying anything. This is exactly the extra context descriptions should 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?

Front-loads the verb+resource in the first clause, then packs limits and constraints into a dense sequence of semicolon-separated clauses. No sentence is wasted, though the constraint stream is heavily compressed into run-on phrasing rather than being structured into discrete facts.

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 2-parameter tool with no output schema, the description covers what is produced (raw Evidence), what will not happen (no execution, no business conclusions), and the resource limits. It leaves the return shape and source_paths format implicit, but nothing critical to invoking it correctly is missing.

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 coverage is 50%: study_id is documented in-schema but source_paths has no schema description. The description compensates by explaining source_paths' purpose (narrowing scope for large apps) and tying paths to a JS directory. It still omits the array/30-item bounds and the exact path format, so it is helpful but not complete.

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+resource combination: running the built-in syntax scanner over the unpacked JavaScript directory of the current research, and saving raw Evidence. This clearly distinguishes it from siblings like research_read_source or research_import_analysis. An agent knows exactly what operation is performed.

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?

Gives real scoping context: only standard JS, no JSX/TS/ASAR/.app, and advises providing source_paths to narrow scope for large apps. It excludes unsupported input types but never names an alternative tool to use for TS/JSX targets, so routing is implied rather than explicit.

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