Seguidores por período

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

No annotations are provided, so the description carries the full burden. It discloses meaningful behavioral context: it combines organic+paid data, covers both Facebook and Instagram, allows per-asset or portfolio consolidation, and computes gains/losses/balance/accumulated total. However, it does not disclose return format, auth needs, rate limits, or edge cases, leaving moderate gaps.

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 two sentences, front-loaded with the core purpose and key options. Every word adds value: metrics, granularity, data mix, platform coverage, and aggregation mode. No filler or redundancy, and the structure is logical.

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 tool has 6 optional parameters and no output schema, so the description must explain return values. It does explain the conceptual output (gains, losses, balance, cumulative) but not the actual response structure, pagination, or how periods are keyed. It lacks enough detail to fully predict the tool's behavior in all contexts.

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 100%, so all parameters are already explained in the schema. The description adds some context by mentioning granularity and consolidation options, but it does not provide new syntax or format details beyond the schema. The baseline of 3 applies; the description reinforces but does not significantly augment parameter semantics.

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 clearly states a specific verb+resource: it shows follower evolution over time with metrics like gains, losses, balance, and cumulative totals. It also distinguishes itself by specifying scope (Facebook/Instagram, per asset or consolidated) and granularity (month/day/week/quarter/year), differentiating it from sibling tools like followers_overview or snapshot_history.

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 usage by describing the time-series analysis, but it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. There is no comparison to sibling tools like followers_overview or snapshot_history, so guidance is only implicit.

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