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/ingramradical235/anty-framework/root-causenpx skills add Ingramradical235/anty-framework --skill root-causegit clone --depth 1 https://github.com/Ingramradical235/anty-frameworkWrote 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/ingramradical235/anty-framework/root-cause)<a href="https://agentmods.dev/skills/ingramradical235/anty-framework/root-cause"><img src="https://agentmods.dev/badge/skills/ingramradical235/anty-framework/root-cause.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 | $0.00063 | $0.01378 |
| Opus 5 | $0.00032 | $0.00689 |
| Sonnet 5 | $0.00013 | $0.00276 |
| Haiku 4.5 | $0.00006 | $0.00138 |
Grade A, and why
root-cause 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 5d 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.
This is a copy
100% identical to root-cause — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Root Cause Analysis (WHERE -> WHY)
When to Apply
- Buffer enters YELLOW or RED zone
- Actions executed but metrics not moving (Layer 1 OK, Layer 2 stalling)
- Significant KPI decline detected
- Review engine Question 5 triggers (was root-cause analysis correct?)
- Any time "why isn't this working?" is asked
Core Framework
Stage 1 — WHERE (Locate the Problem)
MECE decomposition of the underperforming Goal into Drivers, identifying which specific Driver(s) are stalling.
Goal buffer: YELLOW (45% consumed, 34% progress)
WHERE analysis (MECE decomposition by Driver):
Social growth: 45% of target <- GAP HERE
Referral program: 20% of target <- GAP HERE
SEO content: 60% of target (on track)
LP A/B testing: 30% of target (too early)
Nurture emails: 10% of target (not started)
Identified: Social growth and Referral are primary gaps.
WHERE must complete before WHY begins. This is strict and sequential.
Stage 2 — WHY (Causal Structure Diagram)
Starting from the WHERE-identified gap, build a causal structure by asking "Why?" iteratively, one layer at a time. Each node carries a verification status.
Social growth stalling (WHERE-identified gap)
|
+-- Post engagement declining [VERIFIED - analytics data]
| +-- Content not resonating with ICP [HYPOTHESIS]
| | +-- Tone mismatch [HYPOTHESIS]
| | +-- Topic mismatch (features vs pain-points) [VERIFIED]
| +-- Posting at wrong times [DISPROVEN - analytics show optimal]
|
+-- Follower growth rate declining [VERIFIED]
+-- No engagement with other accounts [VERIFIED] <- ACTION TARGET
+-- Algorithm change [UNCONTROLLABLE]
Causal Node Types
| Type | Meaning | Visual |
|---|---|---|
verified |
Confirmed by data/facts | Solid line |
hypothesis |
Not yet verified | Dashed line |
disproven |
Checked and ruled out | Marked X |
uncontrollable |
Outside our control | Marked X |
action_target |
Selected for countermeasure | Highlighted |
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.
- 5d ago First seen · 147 lines · 63 tokens per session scan A 9608011a07ac
root-cause is a skill published in the GitHub repository Ingramradical235/anty-framework (1 stars, last pushed yesterday), licensed MIT. It adds 63 tokens to every session and 1,378 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to root-cause, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
choice-architecture
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confidence
Contextual confidence calibration — DEFLATE for One-Way Doors and RED zones, PROTECT for Two-Way Doors and fundraising, "How does this work step by step?" depth testing, values-to-consequences redirect, unanimity as risk signal. From Knowledge Illusion — overconfidence is sometimes functional. Use when calibrating…
culture-map
Erin Meyer's Culture Map with 8 dimensions, 5 launch presets (US, JP, DE, UK, FR), Layer A agent-user adaptation, Layer B content-target market adaptation, and anti-sycophancy tone calibration per culture. Use when adapting communication style to the founder's culture, localizing content for target markets, or when…
failure-essence
4 strategic failure patterns from Essence of Failure — dual-objective trap (conflict stress test), strategic ambiguity (operationalizability test), withdrawal decision protocol (pre-committed stop conditions, re-present biweekly), assumption provenance auditing (source, verification, load-bearing flag, sample size).…
kpi-tree
KPI tree decomposition from Goal to Drivers, formula-based factorization, impactweight assignment and dynamic update, Crux identification via importance x tractability, constraint Driver identification, input vs output metric classification. Use when decomposing Goals, prioritizing Drivers, or re-evaluating impact…
network-effects
Andrew Chen's Cold Start Problem framework — atomic network definition with thresholds by product type, anti-peanut-buttering, zero tracking, escape velocity 3-force decomposition (engagement/acquisition/economic), growth ceiling 5-force detection, competitive position dynamics, T2D3 benchmark. Use for products with…