Screwtape.ai

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not describe return format, what false-consensus risk entails, permissions, or mutation/read semantics.

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?

One front-loaded sentence with no wasted words. However, for a three-parameter tool with no annotations, the structure is under-developed rather than fully polished.

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?

No annotations, no output schema, and low schema coverage leave major gaps: task and retain semantics, return values, and usage context are all missing. The single sentence is insufficient for this tool's complexity.

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 33%, with only the answers parameter documented. The description does not explain the task or retain parameters and adds no syntax or format detail beyond the minimal schema text.

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 action: score agreement across several agents' answers and flag false-consensus risk. Clear verb+resource, but does not differentiate from the sibling judge or clarify what consensus scoring adds over judging.

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?

No explicit when-to-use guidance, prerequisites, or alternatives. The description implies a scenario with multiple agents, but does not say when to use this tool versus judge.

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

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses the proof-of-work gate (12 leading zero bits), the nonce format constraint, the rate limit (five keys per IP per UTC day), the auth exemption (no Bearer token or payment), and critically the irreversible return behavior ('returned once,' only the SHA-256 hash stored). These are exactly the traits an agent cannot 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?

It is a tight block of high-value sentences, front-loaded with the action and followed by the hard constraint (pow_nonce) and the operational limits. Minor redundancy exists where the pow_nonce rule is repeated verbatim from the schema, which costs a point, but nothing here is filler.

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 creation tool with no output schema and no annotations, the description covers everything an agent must know: input constraints, auth requirements, rate limits, and the one-time nature of the returned secret plus what is persisted. Nothing material is left unstated.

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 three parameters are already documented in the schema, including the full pow_nonce rule. The description restates the nonce requirement and the optionality of email/name rather than adding new meaning such as date-format edge cases or how name is used server-side. Baseline 3 applies when the schema does the heavy lifting.

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 opens with a specific verb+resource: 'Create a free-tier API key with no human approval,' which is unambiguous about the action and the artifact produced. It loses a point because the tool name 'get_api_key' implies retrieval, so the description is silently correcting the name rather than the name and description reinforcing each other. No sibling differentiation is needed since 'consensus' and 'judge' are unrelated.

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?

It gives clear operating context an agent needs before calling: no human approval, no Bearer token, no payment, and a free tier. It does not state when NOT to use it or point to any alternative for key management, but the surrounding siblings make that unnecessary. This is solid context without explicit exclusions.

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

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

With no annotations, the description carries the full behavioral burden, yet it discloses nothing about determinism, cost, latency, or what happens to the inputs. The retain/API-key behavior exists only in the schema, not the description, so the description adds no behavioral context beyond the return shape.

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?

A single front-loaded sentence with no filler; the verdict domain and return payload come first. It is efficient, though the brevity contributes to the coverage gaps elsewhere rather than earning extra credit.

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?

Five parameters at 20% schema coverage, no annotations, and no output schema means the description should do much more. It hints at the return contents (score, reasons) but leaves criteria, evidence, and the retain behavior unexplained, which is inadequate for a judgment tool with this many inputs.

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 only 20% (just 'retain'), so the description must compensate for task, criteria, evidence, and agent_output, and it does not. It implies score and reasons are outputs but never explains what 'criteria' or 'evidence' inputs mean or how they affect the verdict.

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 ('Return') and resource ('verdict for one agent output'), and even enumerates the verdict domain (pass, fail, retry) plus the payload (score, reasons). The phrase 'one agent output' hints at the single-output scope, but it never names or contrasts the sibling 'consensus', so differentiation is left implicit.

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?

There is no when-to-use or when-not-to-use guidance and no named alternative. An agent must infer from 'one agent output' that this is the single-output counterpart to 'consensus', which is a guess rather than guidance.

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