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

With no annotations, the description carries the full burden. It discloses the measurement window (through 17 Sep 2026), the player population (2,739 established players), and the empirical calibration (red-hot players scored 11% above average; out-of-form 5% below). It also notes 'Per call' and that partial name matches are resolved with the answer naming who was used and who else matched. This is strong behavioral context beyond a simple 'get form' statement.

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 dense but efficient: it packs the metric, scope, date, and calibration into two sentences. The key information is front-loaded (what the tool measures) and the calibration detail is a useful addition. It could be slightly tighter, but every sentence earns its place.

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 single-parameter tool with no output schema, the description is quite complete. It explains the input matching behavior, the population, the date cutoff, and the meaning of the form labels. The only minor gap is that it doesn't describe the exact output structure (e.g., whether it returns a numeric form score or just a label), but the calibration sentence partially covers this.

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 100%, so the baseline is 3. The description adds meaning by explaining that the player parameter accepts partial names and that the answer will disambiguate ('the answer names who was used and who else matched'). This goes beyond the schema's example and clarifies matching behavior, which is valuable for correct invocation.

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 verb and resource: it measures a men's T20 player's current form against their own career average, plus bowling workload and last five appearances. It clearly distinguishes itself from sibling tools like hsh-cricket-matchup or hsh-cricket-momentum by naming the exact metric (red-hot to out-of-form) and the player scope (2,739 established players through 17 Sep 2026).

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 description implies when to use this tool: when you need a player's form relative to their own average, bowling workload, and recent appearances. It doesn't explicitly name alternatives or exclusions, but the specificity of the metric and the mention of 'Per call' provide clear context. A small gap: it doesn't say when NOT to use it (e.g., for team-level analysis or other cricket tools).

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