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 agentmods add skills/theagenticguy/erpaval/customer-researchnpx skills add theagenticguy/erpaval --skill customer-researchgit clone --depth 1 https://github.com/theagenticguy/erpavalWrote 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/theagenticguy/erpaval/customer-research)<a href="https://agentmods.dev/skills/theagenticguy/erpaval/customer-research"><img src="https://agentmods.dev/badge/skills/theagenticguy/erpaval/customer-research.svg" alt="Measured on agentmods" 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 | $0.00113 | $0.01610 |
| Opus 5 | $0.00056 | $0.00805 |
| Sonnet 5 | $0.00023 | $0.00322 |
| Haiku 4.5 | $0.00011 | $0.00161 |
Grade A, and why
customer-research 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 6d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Contents
| File | Path | When to load |
|---|---|---|
| Research design method | ${CLAUDE_PLUGIN_ROOT}/skills/product-design-shared/references/research-design.md |
Hypothesis + null + MECE + findings |
| Pyramid composition | ${CLAUDE_PLUGIN_ROOT}/skills/product-design-shared/references/pyramid-principle.md |
Where findings get composed into arguments |
| Canonical Working Backwards reference | ${CLAUDE_PLUGIN_ROOT}/skills/product-design-shared/references/working-backwards.md |
Listen + Define stage context |
| Research methods | references/research-methods.md |
Interview protocols, affinity clustering, qual/quant taxonomy |
| Customer-insights role | ${CLAUDE_PLUGIN_ROOT}/skills/working-backwards/references/roles/customer-insights.md |
Researcher agent for Listen-stage execution |
| Research plan template | templates/research-plan.md |
Hypothesis, null, MECE questions, methods, findings (fill-in) |
| Problem statement template | templates/problem-statement.md |
"Today [customers] have to..." |
| Customer journey map template | templates/customer-journey-map.md |
Phase / action / touchpoint / thought / feeling / opportunity |
Customer Research
The discipline of framing a testable hypothesis, gathering evidence via MECE sub-questions, and synthesizing findings into a shape the Pyramid Principle can compose. This is the research bottom-up half of Minto's core instruction — the upstream of working-backwards and any narrative composition.
What ships with it
4 files 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.
- 6d ago First seen · 112 lines · 113 tokens per session scan A e6ddebeb3d66
customer-research is a skill published in the GitHub repository theagenticguy/erpaval (28 stars, last pushed 3mo ago), licensed MIT. It adds 113 tokens to every session and 1,610 once invoked, about $0.0006 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 2026-08-30.
Other skills, from other repositories
review
Use when DISCOVER or REFRESH has surfaced a proposal staged at -context.proposed/, to inspect it and record sign-off before applying it.
status
Use when picking up a contextualizer after a gap, or checking reference freshness and pending review work at a glance — read-only, safe to run anytime.
discover
Use when a contextualizer's reference coverage needs to grow against its registered sources — a fresh contextualizer's first pass, quarterly upkeep, or whenever the catalog is lagging what users are asking — to propose new reference files.
new-reference
Use when a single topic is already identified and a full DISCOVER pass would be overkill, to register one new reference in an existing contextualizer.
refresh
Use when an existing contextualizer's references may have drifted from current upstream state — typically weekly, or whenever a few days of upstream changes have accumulated — to bring them back into agreement.
using-skill-engine
When the user mentions skill-engine or "the engine" without naming a specific workflow, or wants first-run setup. Inspects .claude/skills/-context/ install state (and any pending -context.proposed/ proposals) across all three install levels, then dispatches to engine-bootstrap when no contextualizer exists, to…