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/dmzoneill/redhat-ai-workflow/memorygit clone --depth 1 https://github.com/dmzoneill/redhat-ai-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 | $0.00000 | $0.00506 |
| Opus 5 | $0.00000 | $0.00253 |
| Sonnet 5 | $0.00000 | $0.00101 |
| Haiku 4.5 | $0.00000 | $0.00051 |
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 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/memory
View and manage the persistent memory system.
Overview
View and manage the persistent memory system.
Underlying Skill: memory_view
This command is a wrapper that calls the memory_view skill. For detailed process information, see skills/memory_view.md.
Arguments
| Argument | Required | Description |
|---|---|---|
section |
No | - |
Usage
Examples
## Options
View specific sections:
## Actions
Clear completed items:
Add a follow-up task:
Process Flow
This command invokes the memory_view skill. The process flow is:
flowchart LR
START([User runs /memory]) --> VALIDATE[Validate Arguments]
VALIDATE --> CALL[Call memory_view skill]
CALL --> EXECUTE[Execute Skill Steps]
EXECUTE --> RESULT[Return Result]
RESULT --> END([Complete])
style START fill:#6366f1,stroke:#4f46e5,color:#fff
style END fill:#10b981,stroke:#059669,color:#fff
style CALL fill:#3b82f6,stroke:#2563eb,color:#fff
For detailed step-by-step process, see the memory_view skill documentation.
Details
Instructions
skill_run("memory_view")
Options
View specific sections:
# Just current work
skill_run("memory_view", '{"section": "work"}')
# Just follow-ups
skill_run("memory_view", '{"section": "followups"}')
# Just environments
skill_run("memory_view", '{"section": "environments"}')
# Just patterns
skill_run("memory_view", '{"section": "patterns"}')
Actions
Clear completed items:
skill_run("memory_view", '{"action": "clear_completed"}')
Add a follow-up task:
skill_run("memory_view", '{"action": "add_followup", "followup_text": "Review MR !1234", "followup_priority": "high"}')
Clean old session logs:
skill_run("memory_view", '{"action": "clear_old_sessions"}')
Related Commands
(To be determined based on command relationships)
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 · 104 lines · 0 tokens per session scan A 5dc8fd7afa6f
memory is a command published in the GitHub repository dmzoneill/redhat-ai-workflow (5 stars, last pushed 22d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 506 tokens. 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
objective-create
Create a structured objective through guided conversation.
pr-address
Address PR review comments on current branch.
git-pr-push
Create git commit and push branch as PR using git + GitHub CLI.
objective-next-plan
Create an implementation plan from an objective step.
analyze_diamond_feedback
Fetches all comments for the PR associated with the current branch, identifies feedback from Diamond review tool, analyzes it, and presents a plan to address the issues.
objective-update-with-landed-pr
Update objective issue after landing a PR.