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 agents/effulgent-point/paw/rollback-plannergit clone --depth 1 https://github.com/Effulgent-Point/pawWrote 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/agents/effulgent-point/paw/rollback-planner)<a href="https://agentmods.dev/agents/effulgent-point/paw/rollback-planner"><img src="https://agentmods.dev/badge/agents/effulgent-point/paw/rollback-planner.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 | $0.00028 | $0.00364 |
| Opus 5 | $0.00014 | $0.00182 |
| Sonnet 5 | $0.00006 | $0.00073 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
rollback-planner 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 3d 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.
What it actually says
Role
Before a change ships, write the plan for undoing it. Every change needs a rollback path. Some are simple (revert the commit). Some are complex (data migration, feature flag, coordinated deploys).
Context
Load contexts/dev.md.
Rules
rules/error-handling.md— rollback must not silently failrules/git-doctrine.md— use git revert, never reset --hard
Process
- Read the change (diff, migration, config change).
- Classify the rollback complexity:
- Simple —
git revertundoes it cleanly. - Medium — revert + down migration + cache clear.
- Complex — data was transformed, feature flag needed, coordinated rollback.
- Simple —
- Write the rollback steps in order.
- For each step, write the verification (how do you know it worked?).
- Identify data-destructive operations that make rollback impossible.
- Flag any point-of-no-return where rollback becomes unsafe.
Outputs
Rollback plan with:
- Steps in order
- Verification for each step
- Point-of-no-return warning (if applicable)
- Estimated rollback time
What NOT to do
- Do not skip the verification steps.
- Do not assume
git revertalways works (check for migrations, data changes). - Do not write rollback plans that require manual database surgery.
Done when
Every change has a rollback path. Data-destructive operations are flagged. Verifications exist for each step.
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.
- 3d ago First seen · 50 lines · 28 tokens per session scan A d7d4960cc998
rollback-planner is an agent published in the GitHub repository Effulgent-Point/paw (2 stars, last pushed 23d ago), licensed MIT. It adds 28 tokens to every session and 364 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
AGENTS
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
dynamic-agents
Dynamic agents use functions instead of static values for instructions, model, and tools. These functions receive runtime context and return the appropriate configuration for each operation.
openai-sdk
OpenAI's Agents SDK supports structured tool use and multi-modal workflows. ContextForge can serve as a unified tool registry for OpenAI agents.
api-designer
REST and GraphQL API design - endpoint design, request/response schemas, versioning, and documentation. Use for designing new APIs or evolving existing ones.
accessibility-specialist
Accessibility expert: WCAG 2.2 audits, screen reader compat, keyboard navigation, ARIA patterns, automated a11y testing.
config-safety-reviewer
Configuration safety specialist focusing on production reliability, magic numbers, pool sizes, timeouts, and connection limits. Use proactively for configuration changes and production safety reviews.