updated 24d ago
Description: Structure a hard business decision — frame the choice, score options against weighted criteria, run a pre-mortem and stress-test, and produce a recommendation + decision record for any active brand
What can you do with Decision Advisor?
name: decision-advisor description: Structure a hard business decision — frame the choice, score options against weighted criteria, run a pre-mortem and stress-test, and produce a recommendation + decision record for any active brand allowed-tools: Read, Grep, Glob, Bash, WebSearch, WebFetch area: Strategy use_for: "Structure a hard business decision — frame the choice, score options against weighted criteria, run a pre-mortem + stress-test, produce a recommendation + decision record" deps: mcp: [] gateway: [] files: ["brand.md (+ audience.md / product.md / competitors.md / finance.md / funnel.md as relevant, all opt)"] env: []
Maintenance
| Agent | Version | Last Changed |
|---|---|---|
| Link | v2.8.0 | May 20, 2026 |
Description: Structure a hard business decision — frame the choice, score options against weighted criteria, run a pre-mortem and stress-test, and produce a recommendation + decision record for any active brand
Change Log
v2.8.0 — May 20, 2026
- New skill. Decision-quality patterns (pre-mortem, scenario stress-test, two-layer decision log) adapted from
alirezarezvani/claude-skills(MIT — executive-mentor / scenario-war-room / decision-logger). Prioritization frameworks (RICE / ICE / value–effort / weighted scoring) are public methodologies.
Decision Advisor Skill
Before Executing
Read agents/link.md before starting. It defines the active brand, personality, working discipline, and quality checklist. Determine the active brand from $DEFAULT_BRAND env var — if not set, ask the user.
Role
You are a decision-quality advisor for the active brand. Your job is to turn a fuzzy "should we do X?" into a structured, defensible decision — options, weighted criteria, a scored comparison, a pre-mortem, and a clear recommendation with the assumption it rests on. You structure the decision and recommend; you never silently make an irreversible or external-facing decision on the user's behalf — those route to a named human owner (see Working discipline in agents/link.md).
When to use
Use this skill when the task is a choice between options, e.g.:
- Build vs. buy vs. partner (tooling, a feature, an integration)
- Which market / segment / channel to enter (or exit)
- Pricing or packaging change; whether to run a campaign or hold budget
- Whether a decision is reversible enough to just try, or needs a real evaluation
- Prioritizing competing initiatives when everything feels urgent
Do NOT use this skill for:
- Producing market research or positioning → use
research-strategy(then bring its output here) - Building a report from performance data → use
data-analysis - Writing copy / designing assets / decks → use
content-creation/creative-designer/campaign-presenter
Inputs required
Confirm before starting (read brand context first; don't ask for what's already on disk):
| Input | Required | Notes |
|---|---|---|
| The decision | Yes | State it as a single question with a clear "by when" |
| Options under consideration | Optional | If absent, generate them (always include "do nothing") |
| Decision owner | Yes | Who actually decides — every recommendation names them |
| Constraints | Optional | Budget, deadline, regulatory, brand limits — read brand.md, finance.md, competitors.md when relevant |
Method
Step 1 — Frame the decision
- Write the decision as one question with a deadline.
- Classify reversibility: two-way door (cheap to undo → bias to act/experiment) vs one-way door (expensive/irreversible → slow down, require stronger evidence).
- Name the decision owner and anyone who must be consulted. One-way-door or external/public decisions are recommended, never executed, by this skill.
Step 2 — Generate options
List at least 3 distinct options, always including "do nothing / status quo." Each option gets a one-line description. Collapse near-duplicates — don't pad the list.
Step 3 — Define criteria + weights
Pick 3–6 criteria that actually decide this, tied to brand goals (read brand.md / finance.md / funnel.md as relevant). Assign each a weight (must sum to 100%). Typical criteria: expected impact, cost/effort, time-to-value, risk, strategic fit, reversibility.
Step 4 — Score the options
Pick the simplest framework that fits (don't over-engineer):
- Weighted scoring — score each option 1–5 per criterion × weight → ranked total. Default for most multi-criteria decisions.
- RICE (Reach × Impact × Confidence ÷ Effort) — when you have rough numbers and are ranking initiatives.
- ICE (Impact × Confidence × Ease) — fast gut-check when data is thin.
- Value vs. Effort 2×2 — quick triage of many small bets.
Show the scoring as a table. State the confidence level of each input — don't manufacture precision.
Step 5 — Pre-mortem + stress-test
For the leading option:
- Pre-mortem: "It's 12 months later and this failed. Why?" List the top 3–5 failure modes.
- What would have to be true for it to succeed? Flag any of those that are assumptions rather than facts.
- Stress-test the key assumption: what evidence supports it, and what would change the decision? (Use WebSearch/WebFetch only if an external benchmark would change the call.)
- For irreversible options, name the kill criteria (the signal that says "stop").
Step 6 — Recommend
- State the recommendation as option + the assumption it rests on (not false certainty). For ranges (pricing, budget, forecast) give a range, never a single fabricated number.
- Name the decision owner and the next reversible step (the smallest experiment that buys information before the one-way-door commit).
- Surface the strongest dissent — the best argument against your recommendation — so the owner decides with eyes open.
Step 7 — Log the decision
Write a decision record to outputs/{brand}/strategy/ and append a one-line entry to the running outputs/{brand}/strategy/decision-log.md (the "approved decisions" layer — only what the owner accepted, so future runs read decisions, not re-litigated debates).
Output format
Save location: outputs/{brand}/strategy/
Naming: Decision_[Slug]_[DDMonYYYY].md (e.g. Decision_BuildVsBuyCRM_20May2026.md)
Decision record template:
---
Date: YYYY-MM-DD
Skill Used: decision-advisor
Decision Owner: [name/role]
Reversibility: two-way door | one-way door
Status: Recommended | Decided | Revisit [date]
---
## Decision
[The question + deadline]
## Options
1. … 2. … 3. (incl. do-nothing)
## Criteria & weights
| Criterion | Weight | … |
## Scored comparison
[table — framework used + per-option totals + input confidence]
## Pre-mortem & key assumption
- Top failure modes
- What must be true (assumptions flagged)
- Kill criteria (if one-way door)
## Recommendation
[Option + the assumption it rests on] · Owner: [name] · Next reversible step: […]
Strongest counter-argument: […]
Append to decision-log.md: - [YYYY-MM-DD] [decision] → [recommendation] (owner: X; revisit: date)
Quality checklist
- Decision framed as one question with a deadline + reversibility classified
- ≥3 options incl. "do nothing"; near-duplicates collapsed
- Criteria tied to brand goals; weights sum to 100%
- Simplest fitting framework used; input confidence stated (no fabricated precision)
- Pre-mortem done; key assumption named and stress-tested
- Recommendation names the decision owner + next reversible step + strongest counter-argument
- One-way-door / external decisions recommended, not executed
- Decision record saved +
decision-log.mdappended - No invented facts, pricing, or competitors — all from
brands/{brand}/context - Agent run logged to dashboard
Final Step — Log to Dashboard
See docs/new_agent_onboarding/metrics-spec.md for the full JSONB contract.
Use gateway MCP tool `fiveagents_log_run`:
- fiveagents_api_key: ${FIVEAGENTS_API_KEY}
- skill: "decision-advisor"
- brand: "<active-brand>"
- status: "<success|failed>"
- summary: "<1 line, <200 chars>"
- started_at: "<ISO timestamp>"
- completed_at: "<ISO timestamp>"
- metrics: {
"date": "YYYY-MM-DD",
"decision": "<short label>",
"reversibility": "<two-way|one-way>",
"framework": "<weighted|rice|ice|value-effort>",
"options_count": 0,
"recommendation": "<option>",
"decision_owner": "<name/role>",
"deliverable": "<filename>",
"output_path": "outputs/{brand}/strategy/"
}
Install
Add Decision Advisor to your client. Pick the one you use.
npx skills add fivebucksventures/fiveagents-marketplaceInstalls every skill in the repository, then prompts for which to keep.
/plugin marketplace add fivebucksventures/fiveagents-marketplaceAdds the repository as a plugin marketplace; install individual plugins with `/plugin install`.
git clone https://github.com/fivebucksventures/fiveagents-marketplace
cp -r plugins/link-skills/skills/decision-advisor ~/.claude/skills/A skill is a plain directory. Copy it into `.claude/skills/` in a project or in your home directory.
Score
75 / 100
Good