Skill trend

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

Annotations already cover the read-only/idempotent safety profile, and the description goes far beyond them: it discloses the sampling method (points pages of 50 projects spread across history), that all statuses are included, currency (Toman), and a hard coverage limit (newest 10000 projects reachable). These are non-obvious behaviors an agent could not infer from the schema.

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-loaded with the core purpose, then method, then the sibling pointer — a sensible reading order with little filler. It is on the longer side, and the return-value list could be tightened, but every clause carries operational information.

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?

There is no output schema, and the description compensates by enumerating what each sample reports (period covered, posting rate per month, median budget, median bids). Combined with the sampling and reach limits, an agent has enough to decide whether the answer will be reliable.

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 would be 3, but the description adds real meaning: it explains that `points` is how many historical moments are sampled, each covering 50 projects, and that `skill` must be a single skill from pn_skills. That clarifies the practical effect of `points` beyond its min/max bounds.

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 and resource — how demand and budgets for one skill changed over time on Ponisha — and scopes it to a historical, sampled view rather than a live snapshot. This clearly separates it from pn_market, which the description explicitly names as the tool for today's numbers.

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 named use cases ("is demand for X growing", "what did X pay a year ago") and an explicit alternative for a different need (use pn_market for today's numbers). It also warns that it samples across the whole history including all statuses, so an agent knows what it is and is not getting.

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