Scale Capability Match

• Source: Built by Jonathan Kvarfordt. Standalone bundle v0.2.
• Frameworks applied: Step 3. Align

It covers a job one of the eight revenue seats has to finish, and it states its process, decision rules, and output format clearly enough for an agent to follow.

Known weakness, published as found: This skill reads template files that ship in the kit download. Get the full kit so the templates are in place.

1. 1.Copy the SKILL.md text below, or download the raw file.
2. 2.Create a folder named exactly scale-capability-match in your agent's skills directory.
3. 3.Save the file inside that folder as SKILL.md.
4. 4.Ask the agent one of the trigger requests below.
5. 5.Check the output against what you already know before it leaves your desk.

• what kind of AI do we need
• match capabilities
• which AI category

---
name: scale-capability-match
description: Maps a friction point to the AI capability chain it needs (classification, summarization, generation, extraction, search and retrieval, orchestration), sets the OAR level, runs the 4 Ps, and checks readiness. Use when the user says "what kind of AI do we need", "match capabilities", "which AI category", "are we ready for this", or after scale-ai-gate returns AI candidate.
---

# scale-capability-match

Write the Capability section of `artifacts/scale-capability-decision.md`. You don't buy a tool. You buy a capability chain aimed at an outcome.

## Preflight (every run)
1. Confirm `GTM-AI-OS/` is accessible. If not: "I need access to your GTM-AI-OS folder. Select it in Cowork's folder picker, or run `os-install` from the core plugin." Stop until it is.
2. Read `CLAUDE.md`, `INDEX.md`, and the last 20 lines of `signals/log.md`.
3. Check the prerequisites below. For anything missing, ask the cold-start questions and offer: (a) run the earlier skill now, or (b) fast path: answer the questions and this skill writes a minimal version of the missing artifact marked `status: draft (fast path)`.
4. On finish, update the artifact row in `INDEX.md` and append one line to `signals/log.md`: `<date> | <skill> | <produced> | <human changed> | <open question>`.

## Prerequisites
- Gate verdict = AI candidate in `artifacts/scale-capability-decision.md`.
- `artifacts/scale-friction-map.md` and `artifacts/scale-five-whys.md`.
Cold-start: "Paste the friction point and its root cause in two sentences." Continue with those marked fast path.

## Step 1: Name the chain
For the friction point, select the capabilities needed and put them in execution order. Use `references/capability-map.md` for the pain → capability patterns. Example: slow QBR prep = search and retrieval → extraction → summarization → generation.

## Step 2: OAR level
Optimize (time back), Amplify (revenue-linked, proactive), Reinvent (changes the model). Recommend the lowest level that solves the friction. Most teams haven't finished Optimize; say that if relevant.

## Step 3: Human in the loop
Classify the work: pothole (repetitive, low risk: more AI), road (repeatable process: mixed), bridge (complex, high stakes: more human). Outbound to prospects is a road with brand risk, never a pothole.

## Step 4: The 4 Ps
Score 1 to 5: Possibilities (how big is the outcome it could enable), Probability (how likely it works here), Payoff (dollar impact from the friction map), Perspiration (adoption effort the team owes). High payoff with high perspiration is a warning, not a plan.

## Step 5: Readiness
Score 1 to 5: data (from `scale-data-inventory`), integration, governance, feedback loop. Any 1 or 2 becomes a prerequisite listed in the decision.

## Step 6: Expected outcome
Write the sentence: "If we deploy <chain> at <OAR level> on <friction>, we expect <metric> to move from <baseline> to <target> in <window>."

## Step 7: Write
Fill the Capability section. Update `INDEX.md`.

## Hand off
Say: "Now decide how to get the capability. Run `scale-vendor-scorecard`."

What does the Scale Capability Match skill do?

Maps a friction point to the AI capability chain it needs (classification, summarization, generation, extraction, search and retrieval, orchestration), sets the OAR level, runs the 4 Ps, and checks readiness.

Where does the Scale Capability Match skill come from?

Built by Jonathan Kvarfordt. Standalone bundle v0.2.. The source and included files are shown on this page and in the package download.

Why was the Scale Capability Match skill chosen for this library?

It covers a job one of the eight revenue seats has to finish, and it states its process, decision rules, and output format clearly enough for an agent to follow.

When should the Scale Capability Match skill not be used?

Use it only for the job named above. A skill applied outside its scope produces confident output on the wrong question.

How do I install the Scale Capability Match SKILL.md file?

Download the file, create a folder named exactly scale-capability-match inside your agent's skills directory, and save the file inside it as SKILL.md. The agent loads it when a request matches the description.