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 dynos-fit/dynos-work --skill maintaingit clone --depth 1 https://github.com/dynos-fit/dynos-workWrote 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/dynos-fit/dynos-work/maintain)<a href="https://agentmods.dev/skills/dynos-fit/dynos-work/maintain"><img src="https://agentmods.dev/badge/skills/dynos-fit/dynos-work/maintain.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 | $0.00076 | $0.01396 |
| Opus 5 | $0.00038 | $0.00698 |
| Sonnet 5 | $0.00015 | $0.00279 |
| Haiku 4.5 | $0.00008 | $0.00140 |
Grade A, and why
maintain 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 yesterday.
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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dynos-work: Maintain (The Autonomous Backend)
Maintains the long-term health of the repository by proactively identifying and resolving issues before they become blocking findings.
Ruthlessness Standard
- Maintenance work must remove real risk, not generate cosmetic churn.
- Do not open a PR for a shallow fix, a guessed fix, or a fix that was not independently re-checked.
- If a recurring debt cluster is found, name the mechanism that keeps recreating it instead of spraying point fixes.
What you do
Step 1 -- Autonomous Debt Polling (The Trigger)
Every 24 hours (or when invoked), the system performs a Background Meta-Audit:
- Scan the codebase using the Proactive Meta-Auditor.
- Focus on:
- Dependency vulnerabilities.
- Architectural drift (deviations from current "Gold Standards").
- Recurring finding categories from the last 10 tasks.
- Code-smell clusters identified by complexity metrics.
Step 2 -- Severity Threshold Gate
For each discovered finding, determine if it meets the Autonomous Fix Threshold:
- Critical (e.g. Auth/Infra): Immediately proceed to Step 3.
- High (e.g. Security/Performance): Proceed to Step 3.
- Medium/Low: Append to
.dynos/proactive-findings.jsonand wait for the next manual task.
Step 3 -- The Autonomous Fix Pipeline
If a finding meets the threshold, the system starts an Auto-Task:
- Branching: Create a branch
dynos/auto-fix-{finding-id}. - Implementation: Use a specialized Refactor Executor to implement the fix based on the current "Gold Standard" patterns.
- Verification:
- Run the full test suite.
- Spawn a Security Auditor (Opus) to verify the fix.
- Failure Recovery: If audits/tests fail, discard the branch and log the failure to
.dynos/maintenance-log.json. Do not retry more than once.
Step 4 -- The Hand-off (Pull Request)
If the fix passes ALL audits and tests:
- PR Creation: Open a Pull Request (via
gh pr createor similar). - Description: Automatically generate a detailed PR description including:
- The original finding from the meta-audit.
- The "Gold Standard" pattern it followed.
- The audit-pass certificate.
- Notify User: Print:
{timestamp} [MAINTAIN] Autonomous PR created: {pr-url} -- fixed {finding-description}
What ships with it
1 file 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.
- yesterday First seen · 104 lines · 76 tokens per session scan A 2ac6af19a2f8
maintain is a skill published in the GitHub repository dynos-fit/dynos-work (2 stars, last pushed yesterday), licensed MIT. It adds 76 tokens to every session and 1,396 once invoked, about $0.0004 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 2026-09-07.
Other skills, from other repositories
ring:searching-code
Forensic code search and analysis with optional Chain of Draft (CoD) ultra-concise mode. Five-phase methodology (clarification, planning, execution, analysis, synthesis) with severity assessment. Use for targeted investigation of specific patterns, bugs, or vulnerabilities. Skip for broad architecture mapping (use…
ring:using-assert
Using lib-observability/assert, Lerian's runtime assertion package, in two modes. Sweep Mode detects panic()/log.Fatal zero-panic violations, DIY invariant checks, hand-rolled domain predicates, and missing InitAssertionMetrics. Reference Mode catalogs the asserter lifecycle, domain predicates, observability trident…
ring:fixing-lint
Fixing lint to a clean state: runs the linter, groups reported issues into independent streams, and dispatches one parallel fixer agent per stream (ring:backend-go for Go, ring:general-purpose otherwise), iterating until clean. Use when a codebase has lint errors across multiple files. Skip for a single error (fix…
ring:detecting-goroutine-leaks
Detecting goroutine leaks in Go: greps for goroutine patterns, audits goleak coverage (VerifyTestMain/VerifyNone), runs goleak, and dispatches ring:backend-go to fix leaks and add regression tests. Use after implementation or during review when code spawns goroutines or a leak is suspected. Runs before…
ring:test-driven-development
Enforcing the RED-GREEN-REFACTOR loop: write one failing test and watch it fail, write minimal code to pass, then refactor green. Use when starting implementation of a new feature or bugfix, or writing any new production code. Requires pasted failure output as proof of RED; code written before its test must be…
ds-debug
Bug hunter — reproduce the failure as an observed red, localize it (bisect, logs, tracing), test at most three hypotheses, land the minimal fix behind a red-proven regression test, and prove it with the project's own check. Use when something is broken and the cause is not yet known.