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 commands/odinmb/ops-workflow/find-allgit clone --depth 1 https://github.com/OdinMB/ops-workflowWhat 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 | $0.00030 | $0.00618 |
| Opus 5 | $0.00015 | $0.00309 |
| Sonnet 5 | $0.00006 | $0.00124 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
find-all 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 2d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Find All
Run both finder agents in parallel, then brief the user on what the project's gaps mean. Discovery only — no plans, no execution, and the survey list is the only file it writes.
Step 1: Spawn Both Finders in Parallel
Launch two sub-agents simultaneously:
Task finder — spawn a task-finder agent:
Read the task-finder agent instructions at: agents/task-finder.md
Scan depth: full
This is a discovery scan. Do NOT add anything to the backlog, and do NOT write a
follow-up file — return every item you find in your response, with your usual
fields, and let the caller decide what to persist.
Opps finder — spawn an opps-finder agent:
Read the opps-finder agent instructions at: agents/opps-finder.md
Your job: identify 3-5 new directions of work this project should explore.
Stay grounded in the project's goals and limitations from MEMORY.md.
Every suggestion must be something an autonomous agent can start working on.
Step 2: Consolidate and Present
Once both agents complete, brief the user on what the two scans add up to.
Format
No tables. Present 3-6 themes, grouped by what they mean for the project rather than by which finder produced them — e.g. "nobody has checked whether the two biggest funders still take unsolicited applications", "the audience numbers everything else rests on are six months stale". Each theme gets a short paragraph: what is missing or going stale, what it costs to leave it alone, and — where there is a real choice — two directions with what each buys and gives up. Effort labels, lens names, per-item file paths, and the agents' own count lines stay out. Close with the two or three you would start with and why, then ask which to pursue — and where the answer depends on what the user wants the project to achieve, ask that instead of guessing.
Nothing gets dropped: write the complete item list, with the finders' own fields, to plans/YYYY-MM-DD_survey.md — a findings list, not a plan — for whoever plans from it later, and mention that file in one line.
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.
- 2d ago First seen · 51 lines · 30 tokens per session scan A 1f452f5c24de
find-all is a command published in the GitHub repository OdinMB/ops-workflow (7 stars, last pushed 15d ago), licensed MIT. It adds 30 tokens to every session and 618 once invoked, about $0.0002 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 commands, from other repositories
kb-ingest
Esegui un ingest nella LLM Wiki per il progetto o argomento specificato: $ARGUMENTS.
kb-output
Esporta una pagina della LLM Wiki in formato slide deck Marp: $ARGUMENTS.
kb-lint
Esegui un controllo qualità completo della LLM Wiki in $LLMWIKIPATH.
kb-promote
Promuovi il concetto specificato da llm-wiki/wiki/concepts/ alla KB stabile (questo repo o un fork): $ARGUMENTS.
close
Close out a Linear issue — move to Done, add a closing comment, and clean up the local branch/worktree.
entry
Load a Linear issue into context and enter plan mode for a focused session.