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 feasibility-spikegit 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/feasibility-spike)<a href="https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/feasibility-spike"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/feasibility-spike/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/feasibility-spike"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/feasibility-spike.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 | $0.00071 | $0.01128 |
| Opus 5 | $0.00036 | $0.00564 |
| Sonnet 5 | $0.00014 | $0.00226 |
| Haiku 4.5 | $0.00007 | $0.00113 |
Grade A, and why
feasibility-spike 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feasibility Spike
Part of the discovery-phase skill pack ·
validationgroup · readsdiscovery-context.md(runprofile-builderfirst if missing).
Kill the biggest technical risks cheaply. Throwaway by contract.
Step 1 — Read context
Read discovery-context.md (section 3. Engagement → Runner role) and risk-assumption-map.md (anchors the spike to a specific assumption).
If discovery-context.md is missing, ask the BA inline: "who's running the spike — solo BA / BA + engineer / engineering lead?" — tag the output [ASSUMED ENGINEERING]. If risk-assumption-map.md is missing, ask: "name 1–3 feasibility assumptions to test in one sentence each" or proceed as open exploration tagged [EXPLORATION-NOT-SPIKE]. Never block; recommend profile-builder / risk-assumption-mapping for high-stakes work.
Engineering capacity reality-check (warn + confirm, do not halt): if runner is solo BA with no engineering support, warn that the spike will produce a spike-shaped artifact with weak engineering signal. Offer: loop in an engineer, defer the spike to delivery, skip and accept the risk in the proposal, or proceed solo with a ⚠ NO-ENGINEER-OVERRIDE banner at the top of tech-spike-report.md and findings tagged [SPECULATIVE].
Step 2 — State spike goal
One sentence. Tie to a specific assumption from risk-map.
Example: "Prove we can extract structured events from free-text emails with ≥80% precision using a single Claude API call."
Step 3 — Time box
| Tier | When |
|---|---|
| Short — 4 hours | Ruling out a "is this even possible?" question |
| Standard — 1-2 days | Validating a specific approach against representative inputs |
| Escalated — up to 1 week | Genuinely unknown territory; requires explicit BA + engineering lead sign-off |
| >1 week | This is no longer a spike. Re-frame as prototype-plan. |
Stop at the time box. Overrunning spikes are how discovery bleeds into delivery.
Step 4 — Narrowest test
- Use production-representative inputs, not cherry-picked
- Throwaway branch / repo named
spike/<topic>— never merge to main - Prefer manual scripting over frameworks (frameworks hide what you're testing)
- Logging is essential; UI is irrelevant
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 · 94 lines · 71 tokens per session scan A 6ce6e651f78e
feasibility-spike is a skill published in the GitHub repository stanislavnianko/product-discovery-claude-skills (1 stars, last pushed 4mo ago), licensed MIT. It adds 71 tokens to every session and 1,128 once invoked, about $0.0004 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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