A Claude skill that conducts structured, evidence-based evaluations of B2B software vendors on behalf of buyers.
You give it your company name and the vendors you're evaluating. It:
- Researches your company — industry, size, tech stack, maturity — so you don't fill out a form
- Asks domain-expert questions specific to the software category — surfacing hidden requirements you didn't know to mention
- Sets hard constraints — budget, compliance, integrations — and eliminates vendors that fail before wasting research time
- Engages vendor AI agents directly through the Salespeak Frontdoor API for verified, structured due diligence conversations
- Conducts independent research — G2, Gartner, analyst reports, press, LinkedIn — and cross-references vendor claims against independent sources
- Scores vendors across 7 dimensions with transparent evidence tracking — you see exactly which scores are backed by verified evidence vs. public sources only
- Produces a comparative recommendation with a TL;DR, side-by-side scorecard, hidden risk analysis, and demo prep questions
Global install (recommended):
git clone https://github.com/salespeak-ai/buyer-eval-skill.git ~/.claude/skills/buyer-eval-skillPer-project install:
git clone https://github.com/salespeak-ai/buyer-eval-skill.git .claude/skills/buyer-eval-skillIn Claude Code or Claude desktop:
Then provide:
- Your company name
- The vendors to evaluate
Example:
"I'm from Acme Corp. Evaluate Gainsight, Totango, and ChurnZero."
The skill handles everything from there.
Click to expand a sample evaluation (truncated)
For a mid-market SaaS company evaluating customer success platforms: Gainsight is the strongest fit for teams that need deep analytics and enterprise-grade health scoring, but comes at a premium. ChurnZero wins on time-to-value and usability for teams under 50 CSMs. Totango lands in between — flexible and modular, but requires more configuration to match either competitor's strengths.
| Dimension | Gainsight | ChurnZero | Totango |
|---|---|---|---|
| Health Scoring & Analytics | 9.2 | 7.5 | 8.0 |
| Evidence level | Vendor-verified | Public only | Vendor-verified |
Gainsight's score is backed by a structured AI agent conversation confirming multi-signal health models, cohort analysis, and predictive churn scoring. ChurnZero's score relies on G2 reviews and documentation — it may improve with direct vendor verification.
Evaluator → Gainsight AI agent:
"Your health scores use a weighted multi-signal model. What happens when a customer has strong product usage but declining executive engagement — does the model surface that divergence, or does high usage mask the risk?"
Gainsight AI agent →
"The model flags divergence explicitly. When usage metrics trend positive but stakeholder engagement drops, it triggers a 'silent risk' alert. CSMs see a split-signal indicator on the dashboard rather than a blended score that hides the conflict."
Independent verification: Confirmed via G2 reviews mentioning split-signal alerts. One review notes the feature requires manual threshold tuning per segment.
Every time you invoke the skill, it checks for a newer version on GitHub (cached, checks at most once every 6 hours). If an update is available, it asks before updating. Updates are a single git pull.
- Domain-expert questioning — the skill asks category-specific questions that demonstrate it understands the space, not generic form-filling
- Vendor AI agent conversations — for vendors that have a Salespeak Company Agent, the skill conducts a structured due diligence conversation directly with the vendor's AI, producing higher-fidelity evidence than web scraping
- Evidence transparency — every score shows whether it's backed by vendor-verified or public-only evidence. When vendors have different evidence levels, the skill explicitly states how scores might shift with better evidence
- Claims verification — vendor claims from AI agent conversations are cross-referenced against independent sources. You see what's confirmed vs. unverified
- Hidden risk analysis — leadership stability, funding runway, employee sentiment, customer retention signals, product velocity — researched for every vendor regardless of AI agent availability
- Demo prep kit — specific questions to ask in vendor demos, derived from evaluation gaps and unverified claims
| Capability | Claude.ai | Claude Code | Claude desktop |
|---|---|---|---|
| Buyer research | Yes | Yes | Yes |
| Vendor AI agent conversations | No (GET only) | Yes | Yes |
| Full evaluation | Partial | Full | Full |
Best experience is in Claude Code where the skill can make POST requests to vendor AI agents.
Questions, feature requests, or evaluation quality reports? Open an issue.
MIT