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 deciqAI/knowledge-skills --skill sop-systemizationgit clone --depth 1 https://github.com/deciqAI/knowledge-skillsWrote 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/deciqai/knowledge-skills/sop-systemization)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/sop-systemization"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/sop-systemization/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/deciqai/knowledge-skills/sop-systemization"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/sop-systemization.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 | $0.00079 | $0.00671 |
| Opus 5 | $0.00039 | $0.00336 |
| Sonnet 5 | $0.00016 | $0.00134 |
| Haiku 4.5 | $0.00008 | $0.00067 |
Grade A, and why
sop-systemization 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 9d 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SOP Systemization — Turn Repetitive Work into Repeatable Process
Overview
A Standard Operating Procedure captures a recurring task as a documented, repeatable sequence so it can be handed to a person or an AI agent and produce the same result without you. For a founder-bottlenecked business this is the unlock: it converts tribal knowledge in your head into an asset that scales, delegates, and automates. SOPs are also the raw material AI agents need to run a task reliably.
The Process
- Inventory recurring tasks — list what you do repeatedly; rank by frequency × time × how much only-you-can-do-it.
- Pick the highest-leverage repetitive task first. Gate: systemizing rare one-offs is wasted effort — target frequency × time.
- Capture the actual steps while doing it — record/screen-capture the real workflow, including inputs, decisions, and the "done" definition.
- Write it so a novice (or an agent) can execute — explicit steps, decision rules, examples, and a clear output standard. Gate: if it needs your judgment to run, extract the decision rule; don't leave it implicit.
- Test by delegation — have someone/something else run it; fix every gap they hit.
- Assign an owner and a review date — SOPs rot; schedule updates. Then delegate or automate.
When to Use
- Founder is the single point of failure on operations
- Preparing to hire, delegate, or hand tasks to AI agents
- Recurring errors from inconsistent execution
Applying It Well
- Capture while doing the real task, not from memory.
- The clearer the decision rules, the more an agent can run it end-to-end.
- Start with the one task that frees the most founder time.
Red Flags
- Documenting rare tasks while daily bottlenecks stay in your head.
- SOPs vague on decisions/output standard (can't be delegated).
- Written once, never updated.
Verification
- Recurring tasks inventoried and ranked by leverage
- Top task captured from the real workflow
- Steps + decision rules + output standard explicit
- Validated by someone/something else running it; owner assigned
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.
- 9d ago First seen · 44 lines · 79 tokens per session scan A 575789a0d317
sop-systemization is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 11d ago), licensed MIT. It adds 79 tokens to every session and 671 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 2026-09-03.
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