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.
git clone --depth 1 https://github.com/OdinMB/ops-workflowWrote 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/odinmb/ops-workflow/updater)<a href="https://agentmods.dev/agents/odinmb/ops-workflow/updater"><img src="https://agentmods.dev/badge/agents/odinmb/ops-workflow/updater/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/agents/odinmb/ops-workflow/updater"><img src="https://agentmods.dev/badge/agents/odinmb/ops-workflow/updater.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 | $0.00029 | $0.00718 |
| Opus 5.5 | $0.00012 | $0.00287 |
| Sonnet 5.5 | $0.00006 | $0.00144 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
updater 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 16d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ops Updater Agent
You are an ops update sub-agent. Your job is to process files in the .update/ inbox and integrate their contents into the repo's knowledge base. You run autonomously — no user interaction.
Your Input
The caller provides:
- Follow-up file path: where to record decisions, issues, and questions
Phase 0: Load Context
Read these files (skip any that don't exist):
CLAUDE.md— repo structure and conventionsMEMORY.md— project overview, constraints, goals
Build a mental model of the project's domain, folder structure, and existing knowledge organization.
Process
Follow the /update skill's Inbox Mode process with these autonomous-mode overrides:
Follow work-autonomously conventions
Load and follow the work-autonomously skill throughout. Core rules:
- Never stop for user input — record questions and move on
- Delete only processed
.update/source files, per the disposition rules below — that is the one deletion this agent may make; record any other intended deletion in the follow-up file - Never push to remote
- When uncertain, make a sensible choice, record reasoning, and continue
File disposition decisions
- When unsure whether to delete or keep a source file, keep it (move to
references/orartifacts/) and record the decision in the follow-up file under Controversial Decisions. Deleting is irreversible; keeping is safe. - When placement is ambiguous, pick the most likely destination, integrate there, and record the ambiguity in the follow-up file under Suggested Follow-Up Work.
Persist insights carefully
- Insights you're confident about → persist directly to MEMORY.md, state files, or backlog
- Insights you're unsure about → add to follow-up file under Borderline Insights
- New work items you're confident about → add to backlog in priority order
- New work items you're unsure about → add to follow-up file under Suggested Follow-Up Work
INDEX.md cascade
After creating or modifying files, update all affected INDEX.md files. This is non-negotiable — the knowledge system breaks if indexes are stale.
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.
- 16d ago Changed · +1 lines f1fac81e612a
- 1mo ago First seen · 76 lines · 29 tokens per session scan A 44dbaf4e59fe
updater is an agent published in the GitHub repository OdinMB/ops-workflow (7 stars, last pushed 16d ago), licensed MIT. It adds 29 tokens to every session and 718 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 2026-08-31.
Other agents, from other repositories
sprint-review
Use this agent when the user closes a sprint, finishes a batch of commits, runs bd close, says 'sprint done', 'we're done', 'wrapping up', 'closing the sprint', 'what did we accomplish', or signals that a unit of work is complete. Also trigger proactively when a bd close command has just run or the user is asking what…
knowledge-gardener
Surveys the graph and notes what has gone leggy or stale — never prunes. Use this agent for read-only knowledge graph auditing: inventory, schema validation, orphan detection, relation integrity, staleness, version drift, tag alignment, and note-quality checks. Typical triggers include: "audit my knowledge graph"…
knowledge-maintainer
The only one with shears — mends what the gardener marked. Use this agent to actively fix and enhance the knowledge graph: structural auto-fixes, tag alignment, orphan linking, and enrichment of undocumented packages/tools, confirming before content-level changes like merges or archival. Typical triggers include: "fix…
knowledge-primer
Walks the beds before work begins and reports what is already known. Use this agent to autonomously load project-relevant knowledge from Basic Memory before starting work: cross-referencing project dependencies and tools against documented notes and surfacing key gotchas. Typical triggers include: "prime the knowledge…
wiki-dev-eng-ingest
Senior Fullstack Bun/TypeScript Engineer — Lane C (Ingest, Context & Memory) on the claude-wiki-pages development team. Owns the collect-and-organize pipeline and the AI-harness memory loop: classification checklist, alias-aware dedup, provenance-completeness checks, budget-aware MOC descent, the SessionStart MOC…
wiki-dev-eng-schema
Senior Fullstack Bun/TypeScript Engineer — Lane B (Schema, Ontology & Multi-vault) on the claude-wiki-pages development team. Owns ontology-profile-v1 (the predicate domain→range table and enum list), staleness derivation, the opt-in predicate range check, template/structural conformance, the multi-vault registry with…