Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add stanislavnianko/product-discovery-claude-skills --skill sme-workshopsgit clone --depth 1 https://github.com/stanislavnianko/product-discovery-claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/sme-workshops)<a href="https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/sme-workshops"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/sme-workshops/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/sme-workshops"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/sme-workshops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.01020 |
| Opus 5 | $0.00034 | $0.00510 |
| Sonnet 5 | $0.00014 | $0.00204 |
| Haiku 4.5 | $0.00007 | $0.00102 |
Grade A, and why
sme-workshops scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SME Workshops
Part of the discovery-phase skill pack ·
evidencegroup · readsdiscovery-context.md(runprofile-builderfirst if missing).
Use when direct user access is blocked but the client has people who interact with the user daily — customer success, support, sales, ops, internal tool admins. Their view is proxy evidence: faster to access, lower fidelity than direct.
Step 1 — Read discovery context
Read discovery-context.md (sections 1. Client → Decision-makers, 4. Access & Data → Client SMEs). If no SMEs listed there, ask the BA to list them now and update the context file.
If discovery-context.md is missing, ask the BA inline: "which client SMEs are accessible (names + roles, or 'none yet')?" — tag the output [ASSUMED]. Never block; recommend profile-builder for high-stakes work.
Step 2 — Choose workshop format
| Goal | Format | Duration |
|---|---|---|
| Map a process end-to-end | 1:1 walk-through with the SME closest to the process | 60 min |
| Validate competing hypotheses | Small group (3-4 SMEs) facilitated debate | 90 min |
| Surface edge cases | Asynchronous prompt + 30-min sync | 30 min sync + 1 day async |
| Get pain frequency / severity ranking | Solo intake, then group calibration | 45 min solo + 30 min group |
Step 3 — Pre-workshop prompts (sent 24h before)
Send the SME a 4-bullet brief:
- The problem-canvas one-liner
- "Bring a recent example (last 90 days) where this came up"
- "List the 3 most painful touch-points you've heard about from users in the last quarter"
- "What would 'fixed' look like to you, in user behavior, not feature names?"
Step 4 — Workshop facilitation
- Anchor on stories. "Walk me through the last user who hit this." Same rule as user-interviews — past beats hypothetical.
- Separate observation from speculation. When the SME says "users feel X", probe: "How do you know? Did a user say it, or are you inferring?" Tag accordingly.
- Get artifacts. Screenshots, ticket numbers, recorded call links, internal docs. SMEs hoard these by default; ask explicitly.
- End with disagreements. "Where do you and your team disagree about this problem?" Internal disagreement = signal.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 84 lines · 69 tokens per session scan A b87bc01bf811
sme-workshops is a skill published in the GitHub repository stanislavnianko/product-discovery-claude-skills (1 stars, last pushed 4mo ago), licensed MIT. It adds 69 tokens to every session and 1,020 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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