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timps_podcast_show_notes_writer

Transforms a podcast transcript or outline into SEO-friendly show notes with title, summary, chapter timestamps, key quotes, links, guest bio, and 3 tweet drafts.

Instructions

Turn a podcast transcript / outline into SEO-friendly show notes: title, summary, chapter timestamps, key quotes, links, guest bio, and 3 tweet drafts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestNoPlain-English task or context for the agent.
languageNoPrimary programming language (default: python).python
Behavior3/5

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

With no annotations, the description carries full burden. It describes the generation outcome in detail and implies that the tool creates new content rather than mutating existing data. However, it does not mention whether any input is required from the user, what happens with the generated notes, or any side effects/assumptions about the environment.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence with strong front-loading: existing Tool purpose, source, and deliverables. Every item listed serves the description; no wasted words or irrelevant details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a text-generation tool, the output deliverables are fully enumerated, which is valuable absent an output schema. However, the tool has no annotations, no required parameters, and an oddly unrelated 'language' default; the description does not explain the required parameter contract match to the input context, leaving the tool slightly incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 does not add semantics about how `request` should be structured or that the transcript must be supplied there. It also does not clarify whether the `language` param refers to the podcast language or something else, so the description offers little added parameter guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('turn') and explicitly names the resource ('podcast transcript / outline') and target output ('SEO-friendly show notes'), then enumerates the expected elements. This makes the tool's purpose unmistakable and differentiates it from other writing-related sibling tools like demo_video_script_writer or tech_writer_assistant.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states the input context clearly: use when you have a podcast transcript or outline and want show notes. It does not explicitly say when not to use it or mention alternative siblings, but the context is specific enough to guide selection.

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

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