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 skills/kimgoetzke/coding-agent-configs/persistnpx skills add kimgoetzke/coding-agent-configs --skill persistgit clone --depth 1 https://github.com/kimgoetzke/coding-agent-configsWrote 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/kimgoetzke/coding-agent-configs/persist)<a href="https://agentmods.dev/skills/kimgoetzke/coding-agent-configs/persist"><img src="https://agentmods.dev/badge/skills/kimgoetzke/coding-agent-configs/persist.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 | $0.00047 | $0.00842 |
| Opus 5 | $0.00023 | $0.00421 |
| Sonnet 5 | $0.00009 | $0.00168 |
| Haiku 4.5 | $0.00005 | $0.00084 |
Grade A, and why
persist 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 4d 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.
Core idea
- Context window = RAM (volatile, limited)
- Anything important gets written to disk.
Workflow
Step 1: Determine task type
Before doing any work, determine whether the user's request is primarily about understanding or documenting existing code in the current repository.
- If yes → invoke the
research-codebaseskill instead. Do not continue with this skill.- Examples: "how does the auth flow work?", "document the payment service", "explain the middleware chain", "what classes handle X?"
- If no → continue with Step 2.
- Examples: no argument or "analyse this RFC", "summarise the compliance requirements", "investigate options for a new library", "compare approaches for X"
Step 2: Resolve the argument
If an argument was provided:
- Treat it as the topic/subject to persist — use it to derive
{topic}and proceed to Step 3.
If no argument was provided:
- Summarise the conversation since the last persistence event (i.e. since the last invocation of
persist,planning,planning-mode,research-mode, or any other skill that writes to.ai/). If no such event exists, summarise the entire conversation. - The summary must be structured around learnings, insights, and decisions — not a chronological account of what was said. Extract the substance: what was established, what was ruled out, what trade-offs were identified, what conclusions were reached.
- Derive
{topic}from the subject matter of that conversation segment. - Use the summary as the content to persist.
Step 3: Determine output location
Check whether this skill is being invoked within the context of an existing plan (i.e. you are aware of/working on a plan with a folder under {repo root}/.ai/planning/).
Within an existing plan:
- Store output in
{repo root}/.ai/planning/{existing plan folder}/{yyyy-mm-dd} {topic}.md - Example:
.ai/planning/2026-04-09 refactor-auth-flow/2026-04-10 auth-middleware-analysis.md
Standalone (no existing plan):
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.
- 4d ago First seen · 77 lines · 47 tokens per session scan A bc26d1fc0416
persist is a skill published in the GitHub repository kimgoetzke/coding-agent-configs (2 stars, last pushed 15d ago), licensed MIT. It adds 47 tokens to every session and 842 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.
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