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 debabsah/fable-method --skill fable-debuggit clone --depth 1 https://github.com/debabsah/fable-methodWrote 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/debabsah/fable-method/fable-debug)<a href="https://agentmods.dev/skills/debabsah/fable-method/fable-debug"><img src="https://agentmods.dev/badge/skills/debabsah/fable-method/fable-debug/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/debabsah/fable-method/fable-debug"><img src="https://agentmods.dev/badge/skills/debabsah/fable-method/fable-debug.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 | $0.00085 | $0.00767 |
| Opus 5.5 | $0.00034 | $0.00307 |
| Sonnet 5.5 | $0.00017 | $0.00153 |
| Haiku 4.5 | $0.00009 | $0.00077 |
Grade A, and why
fable-debug 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 1mo 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 — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fable-debug
A bug is a wrong belief, not just a wrong line. Fix your model of the system first; the code change then falls out. Never debug by mutation — "change something, rerun, hope" burns evidence and moves the bug around.
The procedure
- Reproduce first. Get the minimal command that shows it red, and run it. A failure you can't trigger on demand can't be verified fixed — and if you can't reproduce it, that is the finding: report it and instrument (logging, a capture) instead of shipping a speculative patch.
- State the contradiction in one sentence. "X should produce Y because Z; it produces W." If you can't fill in Z, you don't understand the intended behavior yet — go read the source of truth first (R1).
- Run a hypothesis ledger, cheapest-first. List 2–5 candidate causes. Each gets a designed probe with a predicted outcome written down before running it — a probe whose outcome you can't predict is a coin flip, not an experiment. One variable per probe. Strike out falsified rows in writing; that's what prevents circling back to a cause you already killed.
- Bisect the delta when a working/broken pair exists — version, commit, input, environment, config. Differential evidence beats staring at code.
- Three strikes → up a level. The same category of fix failing twice means the shared assumption underneath is wrong (R2). Stop patching; re-read the contradiction; widen the frame.
- Fix the invariant, not the instance. Root cause found → grep every caller and sibling path; the fix goes where all paths route through, or the siblings stay broken.
- Verify red → green on the exact reproduction from step 1 — red before the fix, green after, at the layer of the claim (→ fable-verify). A fix you never watched fail isn't proven to be the fix.
- Root-cause the escape. Always the second question: why did the existing checks miss this? Mint the runnable rule — the test/assert/check that would have caught it — and log the gotcha (
trap → cause → rule) to.fable/project.md. If a task file is open in.fable/tasks/, record the decision trail there. And if the broken behavior was vouched for earlier, find that claim in.fable/claims-log— and in.fable/claims-log.<year>, wherefable-shiparchives older ones; a claim you can't find is not a claim that was never made — then mark itFALSIFIED <date> — <what actually broke>: a falsifiedVerified:is a calibration miss, and how the check missed it is the gotcha.
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.
- 1mo ago First seen · 29 lines · 85 tokens per session scan A aee2a1380292
fable-debug is a skill published in the GitHub repository debabsah/fable-method (1 stars, last pushed 2mo ago), licensed MIT. It adds 85 tokens to every session and 767 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
systematic-debugging
Root-cause-first debugging discipline — build a red-capable feedback loop, minimise the repro, rank falsifiable hypotheses, fix at the source.
error-handling-patterns
Error handling patterns across languages — exceptions, Result types, propagation, graceful degradation.
ci-routing
The canonical route-on-verdict protocol for a red CI diagnosis — fixable/flake/infra/needs-debug handling, the single-render rule, and the fix-then-re-watch loop.
postmortem-writing
Author blameless incident postmortems — timeline, root cause(s), contributing factors, action items.
postgresql-optimization
Write or review PostgreSQL-specific SQL: JSONB, arrays, custom/range/geometric types, indexing, full-text search, window functions, extensions, and RLS.
sentry-cli
Guide for using the Sentry CLI from the command line.