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/fall-out-bug/sdp/ideanpx skills add fall-out-bug/sdp --skill ideagit clone --depth 1 https://github.com/fall-out-bug/sdpWhat 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 | $0.00008 | $0.01274 |
| Opus 5 | $0.00004 | $0.00637 |
| Sonnet 5 | $0.00002 | $0.00255 |
| Haiku 4.5 | $0.00001 | $0.00127 |
Grade A, and why
idea 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 2d 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@idea - Requirements Gathering with Progressive Disclosure
Deep interviewing to capture comprehensive feature requirements using progressive disclosure (3-question cycles). Creates markdown spec, optionally creates Beads task.
EXECUTE THIS NOW
When user invokes @idea "feature description":
Step 1: Read Context
Read existing project files to understand context:
PRODUCT_VISION.md- Align with project goalsdocs/specs/**/*- Similar features
Step 2: Progressive Interview (3-Question Cycles)
Question Target:
- Minimum: 12 questions (bounded exploration)
- Maximum: 27 questions (deep analysis)
- Average: 18-20 questions per feature
3-Question Cycles:
- Ask 3 focused questions
- Offer trigger point after each cycle
- User chooses: continue / deep design / skip to @design
Cycle 1 - Vision (3 questions):
- What is the core mission of this feature?
- How does this align with PRODUCT_VISION.md?
- Who are the primary users?
TRIGGER POINT (after each cycle):
- Continue (more questions)
- Deep design (jump to @design with architectural exploration)
- Skip to @design (move to workstream decomposition)
Cycle 2 - Problem & Users (3 questions):
- What problem does this solve?
- What are the user pain points?
- What happens if we don't build this?
Cycle 3 - Technical Approach (3 questions):
- Storage/data requirements?
- Failure modes to handle?
- Integration points?
Cycle 4 - UI/UX & Quality (3 questions):
- UI/UX requirements?
- Performance targets?
- Security considerations?
Cycle 5 - Testing & Edge Cases (3 questions):
- Testing strategy?
- Edge cases to handle?
- Success metrics?
Step 3: TMI Detection
If user provides extensive detail upfront:
- "detailed spec", "full implementation", "complete architecture"
- User writes >500 characters in initial prompt
Offer shortcuts:
- Continue with targeted questions (recommended)
- Skip to @design with detailed spec
- Use --quiet mode for minimal questions
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.
- 2d ago First seen · 189 lines · 8 tokens per session scan A 185b2c49ba60
idea is a skill published in the GitHub repository fall-out-bug/sdp (19 stars, last pushed 2mo ago), licensed MIT. It adds 8 tokens to every session and 1,274 once invoked, about $0.0000 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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