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 openshift-online/agent-control-plane --skill memorygit clone --depth 1 https://github.com/openshift-online/agent-control-planeWrote 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/openshift-online/agent-control-plane/memory)<a href="https://agentmods.dev/skills/openshift-online/agent-control-plane/memory"><img src="https://agentmods.dev/badge/skills/openshift-online/agent-control-plane/memory/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/openshift-online/agent-control-plane/memory"><img src="https://agentmods.dev/badge/skills/openshift-online/agent-control-plane/memory.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 | $0.00099 | $0.00957 |
| Opus 5.5 | $0.00040 | $0.00383 |
| Sonnet 5.5 | $0.00020 | $0.00191 |
| Haiku 4.5 | $0.00010 | $0.00096 |
Grade A, and why
memory 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 1mo 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.
This is a copy
100% identical to memory — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Management
Manage the auto-memory system for the Ambient Code Platform project.
Usage
/memory # Show summary of all memories
/memory search <query> # Search for a topic
/memory audit # Check for stale/duplicate memories
/memory prune # Remove stale memories (with confirmation)
/memory add <topic> # Create a new memory
User Input
$ARGUMENTS
Parse the subcommand from $ARGUMENTS. Default to summary if empty.
Memory Location
All memory files live at:
$HOME/.claude/projects/<project-slug>/memory/
Use the active project's slug (the repo path with / replaced by -).
The index file is MEMORY.md in that directory.
Subcommands
/memory — Summary
- Read
MEMORY.mdto get the index - Count total memories by type (user, feedback, project, reference)
- List the most recently modified files
- Report: total count, breakdown by type, last modified dates
/memory search <query>
- Read
MEMORY.mdfor the index - Grep through all memory files for the query term
- Read matching files and show relevant excerpts
- Report: matching files with frontmatter (name, type, description)
/memory audit
Check for quality issues:
- Stale memories — project/reference memories older than 3 months may be outdated
- Duplicate memories — similar names or descriptions across files
- Missing frontmatter — files without proper
name,description,typefields - Orphaned files — memory files not referenced in
MEMORY.md - Broken links —
MEMORY.mdentries pointing to nonexistent files - Oversized index —
MEMORY.mdapproaching the 200-line truncation limit
Report each issue with the file path and suggested action.
/memory prune
- Run the audit checks
- Present findings to the user
- For each stale/duplicate/orphaned memory, ask: keep, update, or delete?
- Execute confirmed deletions
- Update
MEMORY.mdindex accordingly
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.
- 1mo ago First seen · 129 lines · 99 tokens per session scan A a2fd9bd480ae
memory is a skill published in the GitHub repository openshift-online/agent-control-plane (12 stars, last pushed today), licensed MIT. It adds 99 tokens to every session and 957 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to memory, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
wiki-ingest
Use when an operation issue asks to ingest a captured raw/ source into the LLM Wiki, or the user says "ingest ". Create durable source, entity, concept, synthesis, index, and log pages; use paperclip-distill for Paperclip bundles.
wiki-lint
Use when an LLM Wiki operation issue is a lint or health check. Audit for contradictions, orphans, weak provenance, broken links, missing concept pages, and index/log drift; return triage findings without auto-fixing.
para-memory-files
Use a file-based PARA memory system to store, retrieve, and organize durable knowledge across sessions. Trigger on saving facts, daily notes, entity records, weekly synthesis, recall, tacit user patterns, or plan memory.
handoff
Write a compact, decision-ready handoff so the next session (or the user) can continue without reconstructing the current one. Use when the session is ending, context is running low, the user asks for a handoff / 'pass the baton' / 'hand off', or a long-running operation needs a durable state checkpoint.
forget
Help the user remove a stored fact using Codewhale's Context Lens when they ask to forget or delete a memory.
context-engineering
Use when designing, reviewing, or debugging how an agent's context window gets filled, pruned, or shared — choosing what loads at boot versus on demand, sizing an install or an always-loaded file, fixing an agent that drifts, repeats itself, or forgets constraints mid-task, planning compaction or summarization…