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rodfinch1-design

servicehawk-ad-intel

record_ad_swipe

Log an observed ad pattern into a local swipe file and score its reusable winning signals to inform future ad research.

Instructions

Record one observed ad pattern into the local swipe file and score its reusable winning signals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoAnalyst notes.
offerYesOffer or CTA, such as free audit, demo, report, or consultation.
formatNoCreative format, such as image, static image, carousel, or video.
headlineYesAd headline or largest visible hook.
verticalNoVertical, such as plumbing, HVAC, reputation management, or local SEO.
page_nameYesAdvertiser/page name.
source_urlNoPublic ad or library URL used as evidence.
active_daysNoObserved active duration if known.
descriptionNoAd description or link preview text.
active_sinceNoObserved start date in YYYY-MM-DD if known.
primary_textNoPrimary ad body text copied from the public ad.
visual_notesYesObserved visual pattern, layout, scene, or creative notes.
seen_repeatedNoWhether this hook/visual pattern appears repeatedly.
variant_countNoNumber of similar variants observed.
landing_page_urlNoLanding page URL if visible.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly indicates a write side effect ('local swipe file') and a scoring behavior, but it does not disclose whether recordings append, overwrite, or require an existing file, nor does it mention permissions or response details.

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?

The description is a single sentence with no filler. It front-loads the core action and resource, and every word contributes to the agent's understanding.

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?

The core action and target resource are clear, and the schema covers parameter details, making the tool callable. However, with no output schema and no annotations, the description does not mention what the tool returns, such as a confirmation, the saved record, or the winning-signal score.

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 description coverage is 100%, so the input schema already fully documents all 15 parameters. The tool description adds no parameter-specific meaning, which is acceptable given the rich schema, yielding the baseline score.

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

Purpose4/5

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

The description states a specific verb ('Record'), resource ('local swipe file'), and adds a secondary behavior ('score its reusable winning signals'), so the agent understands what the tool does. It does not explicitly contrast itself with the sibling score_ad_pattern, which also involves scoring, so it slightly misses full sibling differentiation.

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

Usage Guidelines3/5

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

The phrase 'one observed ad pattern' implies this tool is for capturing a single observation, which provides some usage context. However, there is no guidance on when to prefer this over score_ad_pattern, or whether repeated recordings of the same pattern should be deduplicated.

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