flompt

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the output is 'Claude-optimized,' includes a token estimate, and accepts JSON strings. It lacks explicit mention of input validation behavior or idempotency, but covers the core transformation semantics well.

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?

Uses a structured Args/Returns format that front-loads the essential information. Every sentence earns its place: first defines purpose, second establishes input provenance, Args section documents the parameter, Returns section confirms output characteristics. No redundancy.

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?

Given the existence of an output schema (not shown but indicated in context signals), the description appropriately focuses on input requirements and sibling relationships. It explains the block structure thoroughly and mentions the token estimate feature, providing complete context for a transformation utility with one parameter.

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?

The schema has 0% description coverage (only 'title: Blocks Json'). The description fully compensates by specifying the parameter accepts 'JSON-stringified list of blocks' and details the expected object structure with fields (type, content, label, description, summary) and example values ('role|objective|...').

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 precise action (compile), input (list of blocks), and output (Claude-optimized structured XML prompt). It clearly distinguishes from sibling 'decompose_prompt' by stating this tool performs the inverse operation (assembly vs. decomposition).

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?

Explicitly names the sibling tool 'decompose_prompt' as the expected input source and provides the alternative of 'manually crafted blocks.' This establishes the clear workflow: decompose → [optional edit] → compile.

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 provided, the description carries the full burden. It excellently discloses implementation details ('Uses AI (Claude/OpenAI) if an API key is configured... otherwise falls back to keyword-based heuristic analysis') and return format ('JSON list of blocks'). Minor gap: no mention of error handling for empty prompts or API failures.

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?

Highly structured with zero waste. Information is front-loaded (purpose first), followed by implementation details, then Args/Returns sections. Every sentence earns its place, and the pseudo-docstring format is appropriate for the technical audience.

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?

Complete for a single-parameter tool despite 0% schema coverage. It leverages the existence of an output schema by summarizing returns ('summary of extracted blocks + the full JSON') without over-specifying. The mention of sibling integration and dual-mode operation provides necessary workflow context.

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 0% (parameter has title but no description). The description compensates via the 'Args:' section defining 'prompt' as 'The raw prompt string to decompose.' This provides clear semantics, though it could be elevated to 5 with additional constraints or format examples.

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 ('Decompose') and resource ('raw prompt'), clearly stating the output format ('structured blocks'). It explicitly references sibling tool 'compile_prompt' ('ready to edit or pass to compile_prompt'), establishing the workflow relationship and distinguishing it from 'list_block_types'.

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 provides clear usage context by stating the output is 'ready to edit or pass to compile_prompt', guiding the agent on next steps. It also explains the conditional behavior (API key vs fallback), which informs when the tool operates in different modes. However, it lacks explicit 'when not to use' guidance or comparison to 'list_block_types'.

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?

No annotations provided, so description carries full burden. It adds valuable return value disclosure ('Description of each block type and the recommended canonical ordering'), but fails to explicitly state safety profile (read-only), idempotency, or cost characteristics that annotations would typically cover.

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?

Three tightly constructed sentences: purpose declaration, usage context, and return value. Front-loaded with the core action, zero redundancy. 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?

Appropriate for a simple discovery tool with zero inputs and an output schema (which handles detailed return documentation). Covers the essential domain context ('flompt') and sibling relationship. Deduction only because, lacking annotations, it could explicitly confirm this is a safe, non-destructive operation.

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?

Zero parameters present. Per scoring rules, 0 params = baseline 4. The description correctly does not invent parameter semantics where none exist.

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?

Specific verb ('List') + resource ('block types') + domain ('flompt'). Explicitly distinguishes from sibling 'compile_prompt' by referencing it in usage context, clarifying this is a discovery tool for that compilation target.

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?

Provides clear positive guidance ('Useful to know which types to use when manually crafting blocks to pass to compile_prompt'), establishing the workflow relationship with the sibling tool. Lacks explicit 'when not to use' or alternative enumeration, but the context is sufficient for selection.

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