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 glebis/humane-agentic-design --skill jtbdgit clone --depth 1 https://github.com/glebis/humane-agentic-designWrote 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/glebis/humane-agentic-design/jtbd)<a href="https://agentmods.dev/skills/glebis/humane-agentic-design/jtbd"><img src="https://agentmods.dev/badge/skills/glebis/humane-agentic-design/jtbd.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00168 | $0.04663 |
| Opus 5 | $0.00084 | $0.02331 |
| Sonnet 5 | $0.00034 | $0.00933 |
| Haiku 4.5 | $0.00017 | $0.00466 |
Grade A, and why
jtbd 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 8d 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 — 395 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JTBD Project Describer
Announce at start: "I'm using the humane:jtbd skill to capture the job and its switching forces."
Purpose
Conduct a focused Jobs-to-Be-Done interview for one project and emit a decision-grade artifact bundle. The bundle contains a machine-readable jtbd.json, a shareable one-pager.md, and a messaging-angles.md derived from Switch forces. Ingest voice transcripts or review exports when available.
When to invoke
- "Describe my project in JTBD."
- "Turn this interview transcript into a JTBD brief."
- "Mine these reviews for jobs."
- "I need messaging from this product idea."
- "Help me articulate what I'm actually building."
- "Update my JTBD brief with new data."
- "Decompose this job into outcomes."
- "Generate a GTM brief from this JTBD."
If the user wants a full design spec (what to build, scope, components), prefer skill-studio — it's the heavier tool. jtbd is the quick, rigorous record.
Mode selection
Pick one at the start. Ask the user only if ambiguous.
| Mode | Input | Output |
|---|---|---|
| Interview (default) | live conversation | full artifact bundle |
| Transcript ingest | path to a voice interview transcript | full artifact bundle + confidence flags |
| Review mining | path to reviews (CSV/JSON) | review-brief.md pre-seed → then Interview |
| Update | path to existing <corpus_root>/<slug>/jtbd.json |
updated artifact bundle |
Scope discipline
One project per session. If the user starts describing a second project, stop them: "That sounds like a separate project — let's finish this one first, then run humane:jtbd again for the next."
If the user drifts into implementation details, features, or tech stack: "Interesting, but let's stay at the job level — what is the person trying to accomplish?"
Interview flow
Pass 1 — Core (3–5 adaptive questions, one at a time)
- What is this? — One-sentence description. Push for clarity if vague.
- Who struggles and when? — The triggering situation. "Walk me through the last time this happened."
- What's painful today? — Current workaround and why it's not working.
- What does success look like? — The outcome, not the feature list.
- How should it feel? — Emotional payoff (optional, ask if natural).
What ships with it
31 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.
- .gitignore 34 B
- agents/openai.yaml 118 B
- references/granularity_fixes.md 2.9 KB
- references/jargon_blacklist.md 3.6 KB
- references/job_map.md 2.7 KB
- references/odi.md 3.3 KB
- references/review_taxonomy.md 4.9 KB
- references/superpowers_handoff.md 3.4 KB
- references/switch_forces.md 5.6 KB
- scripts/graph.py 15 KB runs code
- scripts/ingest_transcript.py 9.4 KB runs code
- scripts/mine_reviews.py 15 KB runs code
- scripts/odi_score.py 322 B runs code
- scripts/report.py 18 KB runs code
- scripts/validate_granularity.py 4.0 KB runs code
- scripts/validate_outcome.py 2.3 KB runs code
- templates/data.json 119 KB
- templates/example_bad_then_fixed.json 4.4 KB
- templates/example_good.json 2.2 KB
- templates/graph.html 124 KB
- templates/gtm-brief.md 1.9 KB
- templates/messaging-angles.md 2.0 KB
- templates/one-pager.md 1.1 KB
- templates/review-brief.md 1.4 KB
- tests/test_graph.py 9.8 KB runs code
- tests/test_ingest_transcript.py 13 KB runs code
- tests/test_mine_reviews.py 11 KB runs code
- tests/test_odi_score.py 667 B runs code
- tests/test_report.py 7.8 KB runs code
- tests/test_validate_granularity.py 3.5 KB runs code
- tests/test_validate_outcome.py 1.7 KB runs code
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.
- 8d ago First seen · 395 lines · 168 tokens per session scan A 74a633b9d4d5
jtbd is a skill published in the GitHub repository glebis/humane-agentic-design (28 stars, last pushed 6d ago), licensed MIT. It adds 168 tokens to every session and 4,663 once invoked, about $0.0008 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.
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