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 LucasDuys/forge --skill backpropagationgit clone --depth 1 https://github.com/LucasDuys/forgeWrote 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/lucasduys/forge/backpropagation)<a href="https://agentmods.dev/skills/lucasduys/forge/backpropagation"><img src="https://agentmods.dev/badge/skills/lucasduys/forge/backpropagation/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/lucasduys/forge/backpropagation"><img src="https://agentmods.dev/badge/skills/lucasduys/forge/backpropagation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00027 | $0.02400 |
| Opus 5.5 | $0.00011 | $0.00960 |
| Sonnet 5.5 | $0.00005 | $0.00480 |
| Haiku 4.5 | $0.00003 | $0.00240 |
Grade A, and why
backpropagation 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Backpropagation Skill
You are running the Forge backpropagation workflow. Your job is to trace a runtime bug back to a specification gap, update the spec to close that gap, generate a regression test, and log the correction for systemic pattern detection.
Inputs
You will receive:
- Bug description: Natural-language description of the bug, or test failure output + test source code (from
--from-testmode) - Test file path (optional): Path to the failing test, if
--from-testwas used - Test source code (optional): Contents of the failing test file
- Spec files: List of spec files in
.forge/specs/
Workflow
Step 1: TRACE — Which spec?
Find the spec and requirement that should have prevented this bug.
-
Read all spec files in
.forge/specs/. For each spec, extract:- Domain name (from frontmatter)
- All R-numbered requirements and their acceptance criteria
- The
linked_reposfield (to know which repos are involved)
-
Analyze the bug description (and test failure output if available) to determine:
- What component or feature is affected?
- What behavior went wrong?
- What was the expected behavior?
-
Match the bug to the most relevant spec and requirement:
- Use keyword matching between the bug description and requirement names/descriptions
- Use code context: if the bug mentions specific files, endpoints, or functions, grep the spec for those references
- If
--from-testwas used: read the test source code to understand which feature it tests, cross-reference with spec requirements
-
If no spec appears to cover this area at all, note this as a potential "missing requirement" gap and pick the closest spec by domain.
-
Present your finding to the user:
Traced to:
spec-{domain}.md> R{NNN}: {requirement name} Reasoning: {why this requirement is the match}
Step 2: ANALYZE — What was missed?
Determine exactly what the spec's acceptance criteria failed to cover.
- Read the identified requirement's acceptance criteria in full.
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 · 223 lines · 27 tokens per session scan A f61d3498eda0
backpropagation is a skill published in the GitHub repository LucasDuys/forge (56 stars, last pushed 3mo ago), licensed MIT. It adds 27 tokens to every session and 2,400 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
maintain-formal-verification-skill
Bring a project's formal verification back in line with the code after the code changes: find the commits that touched verified code, update the model, harness, or properties to describe the code as it is now, rerun, and say whether each failure is drift in the verification or a bug in the code. Use for…
evidence-audit
Evidence-led audit/fix rounds for any codebase in any language. Finds only defects that a runnable proof reproduces on current code, applies the narrowest in-scope patch, verifies with a second proof, promotes high-risk proofs to permanent regression tests, and reports exact validation results. Use whenever the user…
debugging
Use this skill when something is broken and the cause is unknown — a failing test, a crash, an error message, wrong output, a regression, a hang, or behaviour that differs between environments — and it has to be found and fixed at the root. Also use it to build the failing proof for a suspected defect before fixing…
prevent-recurrence
Use when correcting an issue or failure reveals a reusable prevention lesson, including code, setup, measurement, validation, workflow, agent mistakes, or accepted code-review findings; when someone says "this keeps happening" or asks how to stop it; or in post-incident follow-up. Fixes the instance (failing-first…
refactor-ops
Safe refactoring patterns - extract, rename, restructure with test-driven methodology and dead code detection. Use for: refactor, refactoring, extract function, extract component, rename, move file, restructure, dead code, unused imports, code smell, duplicate code, long function, god object, feature envy, DRY…
pair-programming
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with…