Validating a signal
Check whether an internal signal is supported by what is happening externally before acting on it.
— Markets & Intelligence
Signals plus research
Deepens a set of internal market signals with live external research, comparing what the signals show against current published evidence.
- Markets & Intelligence
- Traceable reasoning
- Runs anywhere
1 day → ~10 minutes
Including the external research pass
No coding required
- Input
- The signal set to investigate
- Output
- A signals read backed by live external research
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~1 day per run
— USE CASES
What people use Signals plus research for
Deeper market briefings
Combine your own signal data with current research in one evidenced write-up.
Client advisory work
Support a market claim with both signal data and citable external sources.
What it works from
- The signal set to investigate
- The research question or hypothesis
- Any source or scope constraints
What you get back
- A signals read backed by live external research
- Comparison between signal and published evidence
- A briefing others can verify
— HOW IT BEHAVES
How Signals plus research produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Live external research
Current external sources are researched during the run rather than recalled from training data, and the sources travel with the output.
Composed as work product
Findings are written up as a document that reads like professional output rather than raw model text.
Like-for-like comparison
Items are compared on the same dimensions, which makes differences meaningful rather than impressionistic.
Why this is expensive by hand
Signals tell you something is moving; they rarely tell you why. Validating a signal is the typical trigger — check whether an internal signal is supported by what is happening externally before acting on it. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 1 day of manual work.
How this Skill produces it
As a Skill, the work is already sequenced. You bring the evidence, and the run produces a signals read backed by live external research plus comparison between signal and published evidence. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. The practical effect: 1 day of manual work becomes a ~10 minutes run, held to an identical standard on the tenth engagement as on the first.
Who it's for
- Independent consultants codifying their own methodology
- Strategy and transformation teams standardising delivery
- Internal advisory functions under pressure to produce faster
- Operators who need defensible output, not a one-off chat answer
Run it in Skillsize — or export it anywhere
Signals plus research exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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