Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/bks-lab/open-bridgenpx agentmods add skills/bks-lab/open-bridge/bridge-learnWrote 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/bks-lab/open-bridge/bridge-learn)<a href="https://agentmods.dev/skills/bks-lab/open-bridge/bridge-learn"><img src="https://agentmods.dev/badge/skills/bks-lab/open-bridge/bridge-learn/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/bks-lab/open-bridge/bridge-learn"><img src="https://agentmods.dev/badge/skills/bks-lab/open-bridge/bridge-learn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 312 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00074 | $0.03941 |
| Opus 5.5 | $0.00030 | $0.01576 |
| Sonnet 5.5 | $0.00015 | $0.00788 |
| Haiku 4.5 | $0.00007 | $0.00394 |
Grade A, and why
bridge-learn 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 22d 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 — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bridge Learn — Review Surface for Improvement Proposals
/bridge-learn is the Layer-3 edge of the Bridge Learning-Loop architecture
(see work/_learning/README.md). It consumes proposals written by
task-close-postmortem (Phase 1) or /bridge-audit recurring findings
(Phase 3) and walks the user through accept/reject decisions.
Never auto-apply. Every accepted proposal is materialized through a git
commit on user/<name>, audit-trail.md records it, git revert is always
the rollback path.
When to use
| Trigger | Mode |
|---|---|
User says /bridge-learn / "review proposals" / "learn review" |
Interactive — full walk-through |
| /briefing skill invokes (Fridays, when pending ≥ threshold) | Summary — count + 1-line list, no walk |
User says /bridge-learn list |
List-only — no actions, just an overview |
User says /bridge-learn trends |
Trends — recurring + sleeping skills, no proposals |
User says /bridge-learn <proposal-id> |
Single — go directly to that proposal |
Inputs
work/_learning/proposals/*.md— all pending proposalswork/_learning/audit-trail.md— lifecycle log (for statistics)work/_learning/audit-history/— Phase 3, for trends sectionbridge-config.yaml.learning— thresholds (auto_surface_threshold etc.)- (Optional)
work/_learning/skill-usage.jsonl— Phase 4, for "sleeping skills"
Interactive walk-through
Header
═══ Bridge Learning Review — 2026-05-13 ═══
📋 Pending Proposals (N)
P0 <id-1> (<source-type>)
P1 <id-2> (<source-type>)
P2 <id-3> (<source-type>)
...
📈 Trends (last 30d) [if audit-history populated]
Audit findings: P0=0 P1=12→8 P2=23→27 P3=5
Skills inactive: <N> of <total> [if skill-usage populated]
Task estimate-vs-actual: median 1.4x (vs 1.2x last month)
🔁 Recurring patterns (≥3 occurrences)
- <pattern-1> [→ proposal/audit-recurring exists]
- <pattern-2> [new — consider Standing-Order]
→ Review proposals one by one? [y/N]
→ Or: trends / list / quit
What ships with it
2 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.
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.
- 22d ago Changed · -9 lines · -124 tokens per session dce04355f981
- 24d ago Changed · +9 lines 2f5fcf28b4fb
- 25d ago Changed · +36 lines b0bd41ad82bf
- 1mo ago First seen · 319 lines · 198 tokens per session scan A 8543f2373a38
bridge-learn is a skill published in the GitHub repository bks-lab/open-bridge (13 stars, last pushed yesterday), licensed MIT. It adds 74 tokens to every session and 3,941 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.
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