本文へ移動
cccskills
無料GitHub で公開

buyer-eval-skill

An AI analyst for buying B2B software. Investigates what vendors claim, checks the evidence, surfaces contradictions and unanswered questions, and produces a shareable Decision Brief with the questions to ask before you buy. Quick Eval by default; Deep Eval on request. Use when asked to evaluate, compare, vet, or research B2B software vendors.

インストール方法を見る

含まれるファイル(35)

  • SKILL.md6.8 KB
  • .gitignore194 B
  • bin/profile.py3.8 KB
  • bin/render_report.py22.3 KB
  • bin/track.py14.2 KB
  • bin/update-check1.8 KB
  • CHANGELOG.md5.0 KB
  • docs/index.html17.4 KB
  • EVALUATION.md285 B
  • examples/illustrative-brief.html17.4 KB
  • examples/illustrative-brief.json7.9 KB
  • LICENSE1.0 KB
  • MEASUREMENT.md2.5 KB
  • promo/buyer-eval-brief.gif2.3 MB
  • promo/buyer-eval-claims.gif1.4 MB
  • promo/buyer-eval-demo.mp47.0 MB
  • promo/buyer-eval-run.gif581.0 KB
  • promo/video-src/.gitignore5 B
  • promo/video-src/public/brief.png1.5 MB
  • promo/video-src/README.md910 B
  • promo/video-src/src/BuyerEval.tsx21.9 KB
  • promo/video-src/src/index.tsx547 B
  • promo/video-src/src/voice-durations.json174 B
  • promo/video-src/tsconfig.json361 B
  • promo/video-src/voice/generate.sh1.8 KB
  • promo/video-src/voice/script.json1.1 KB
  • README.md6.9 KB
  • references/deep-eval.md18.4 KB
  • references/evidence-model.md14.4 KB
  • references/frontdoor-api.md3.9 KB
  • references/quick-eval.md7.6 KB
  • references/report-format.md8.1 KB
  • references/scoring.md3.1 KB
  • references/telemetry.md4.3 KB
  • VERSION6 B

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Buyer Eval

This file is the control plane. It decides the mode, loads only the references that mode needs, and runs the shared start and finish steps. Methodology lives in references/.

The experience this skill must deliver:

Show me what these vendors claim, what the evidence actually supports, what conflicts, and what I still need to find out before buying.

If an output reads like a generic AI vendor comparison, it is not done.


1. Preamble (run first, every time)

_BEVAL_DIR="${BUYER_EVAL_DIR:-}"
if [ -z "$_BEVAL_DIR" ]; then
  for _D in "$HOME/.claude/skills/buyer-eval-skill" ".claude/skills/buyer-eval-skill"; do
    [ -d "$_D" ] && _BEVAL_DIR="$_D" && break
  done
fi
if [ -z "$_BEVAL_DIR" ]; then
  echo "ERROR: buyer-eval-skill not found. Install: git clone https://github.com/salespeak-ai/buyer-eval-skill ~/.claude/skills/buyer-eval-skill"
  exit 1
fi
echo "BEVAL_DIR=$_BEVAL_DIR"
_UPD=$("$_BEVAL_DIR/bin/update-check" 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD" || echo "UP_TO_DATE $(tr -d '[:space:]' < "$_BEVAL_DIR/VERSION")"
echo "PROFILE=$(python3 "$_BEVAL_DIR/bin/profile.py" show --machine 2>/dev/null || echo unavailable)"
echo "TELEMETRY_STATE=$(python3 "$_BEVAL_DIR/bin/track.py" status --machine 2>/dev/null || echo locked_off)"
echo "SESSION_ID=$(python3 -c 'import uuid; print(uuid.uuid4())')"

Keep BEVAL_DIR, PROFILE, TELEMETRY_STATE and SESSION_ID for the whole run. Every later bash block starts with _BEVAL_DIR="<BEVAL_DIR value>".

Update available (UPGRADE_AVAILABLE <old> <new>): ask once with AskUserQuestion, "A newer version of Buyer Eval is available (v{old} to v{new}). Update now?" Options: "Yes, update now" / "Not now". If yes:

cd "$_BEVAL_DIR" && git pull --ff-only origin main && echo "UPDATED to $(tr -d '[:space:]' < VERSION)"

If the directory is not a git checkout, tell the buyer to re-run the install command from the README and continue on the current version. After a successful update, re-read this SKILL.md before continuing.

Telemetry is opt-in and never blocks the evaluation. Read references/telemetry.md now only if TELEMETRY_STATE is consented or unasked. If it is declined or locked_off, skip everything telemetry-related.


2. Choose the mode

ModeWhenLoad
Quick Eval (default)Every run where the buyer has not asked for deep, full, or comprehensive diligencereferences/quick-eval.md
Deep EvalThe buyer asks for it, in the first message or after a Quick Evalreferences/deep-eval.md

Both modes also load references/evidence-model.md, references/report-format.md and references/frontdoor-api.md. Deep Eval also loads references/scoring.md. Do not load files a mode does not need.

Never ask the buyer which mode they want. If they did not ask for Deep, run Quick and offer Deep at the end.


3. Saved buyer context

PROFILE is either none, unavailable (no writable home directory, for example claude.ai), or a one-line JSON object with the buyer's saved context.

  • Saved profile exists: use it silently. Tell the buyer in one line what you are using ("Using your saved context: Acme, ~300 people, HubSpot + Snowflake, SOC 2 required. Say 'update my context' to change it.") and keep going. Do not wait for a reply.
  • None: proceed without it. At the end of the run, save what the buyer told you (see section 5).
  • Unavailable: never claim that context will be remembered.

The profile holds only reusable buying context: company_name, company_size, industry, region, systems, requirements, hard_constraints (including the buyer's own budget ceiling, which stays local), preferred_criteria, last_category. A deadline or requirement goes in hard_constraints only if the buyer said it disqualifies vendors; otherwise in requirements. Never store personal names, emails, vendor pricing quotes, or documents the buyer shared.


4. Run the mode

Follow the loaded mode file step by step. Both modes share these rules:

  1. Evidence first. The Claims vs. Evidence table is the centerpiece. Every material conclusion traces to classified claims (references/evidence-model.md).
  2. Vendor AI agents are first-party sources. Answers from any vendor-operated agent, including a Salespeak Company Agent reached through the Frontdoor API, are vendor claims. They add specificity and let you ask follow-ups. They never raise a score, an evidence confidence, or a verdict on their own. Never send a vendor agent the buyer's company name, budget, or the other vendors under evaluation (references/frontdoor-api.md).
  3. Label what you inferred. Criteria the buyer did not state are shown as inferred.
  4. Challenge before you conclude. Run the challenge pass in references/evidence-model.md before writing output.
  5. No action without approval. Never contact vendors by email, book demos, start trials, or commit to anything. Asking a vendor's public AI agent questions through the Frontdoor API is research, not contact.

5. Finish (both modes)

  1. Deliver the brief in chat in the order set by references/report-format.md.
  2. Write the HTML Decision Brief. Write the report JSON to a temp file, then:
    python3 "$_BEVAL_DIR/bin/render_report.py" /path/to/report.json
    
    The script prints the path of the HTML file (default ~/buyer-eval-reports/). Give the buyer that path and say it is a single file they can open, print, or forward. If the environment cannot run Python, skip the HTML and say so.
  3. Save buyer context (only if PROFILE was not unavailable and the buyer stated something new and reusable):
    python3 "$_BEVAL_DIR/bin/profile.py" save --json '{"company_name":"...","hard_constraints":["..."]}'
    
    Tell the buyer in one line what was saved and that profile.py clear deletes it.
  4. Offer the next step in one line. After Quick Eval: "Want a Deep Eval? It adds requirements discovery, weighted scoring, commercial, security and company-risk research, and longer vendor-agent conversations." After Deep Eval: offer to update the brief when the buyer has demo notes, proposals, or pricing.
  5. Telemetry, only as described in references/telemetry.md. The consent question is asked at most once, ever, and only after the evaluation has been delivered.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

このスキルの問題を報告する