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delimit_vendor_news_draft

Draft a brand-voice Delimit-POV riff from a vendor-news tweet for the autonomous content queue. Use when a sensor surfaces a tweet warranting a response.

Instructions

Draft a brand-voice Delimit-POV riff for a specific X tweet (Pro) (LED-1253).

When to use: when an operator/sensor surfaces a vendor-news tweet that warrants a Delimit-POV riff for the autonomous content queue. When NOT to use: to fetch the tweet without drafting (use delimit_x_fetch) or for general social drafting (delimit_social_generate).

Sibling contrast: delimit_x_fetch fetches; delimit_vendor_news_health inspects subsystem health; this drafts a riff into the queue.

Side effects: gated by require_premium. Runs the riff drafter end-to-end: rate cap, source-fit pre-filter, generator, capability validator, fit floor, queue insert. dry_run=True suppresses the queue insert but still runs validators (and still consults the 24h per-vendor rate cap to avoid log noise).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tweet_idNoSource X tweet id (numeric string) or full x.com URL. Required.
dry_runNoIf True, suppress queue insertion. Default False.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Without annotations, the description fully discloses side effects: gated by require_premium, end-to-end pipeline steps, rate cap, dry_run behavior. No contradictions.

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

Conciseness4/5

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

Well-structured with sections for purpose, usage, sibling contrast, and side effects. The reference 'LED-1253' is slightly extraneous, but overall efficient.

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

Completeness5/5

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

Covers all needed aspects: purpose, usage, side effects, parameters, siblings. With an output schema present, the description is fully complete for this tool.

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 baseline 3. The description restates parameter purposes but adds minimal new meaning beyond the schema's descriptions.

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 clearly states the tool drafts a brand-voice Delimit-POV riff for a specific X tweet. It distinguishes itself from siblings like delimit_x_fetch and delimit_social_generate by name and contrast.

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

Usage Guidelines5/5

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

Explicit 'When to use' and 'When NOT to use' sections provide clear context, including specific alternative tools (delimit_x_fetch, delimit_social_generate) and conditions.

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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