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.
git clone --depth 1 https://github.com/joseairosa/recallWrote 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/commands/joseairosa/recall/rlm-status)<a href="https://agentmods.dev/commands/joseairosa/recall/rlm-status"><img src="https://agentmods.dev/badge/commands/joseairosa/recall/rlm-status/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/commands/joseairosa/recall/rlm-status"><img src="https://agentmods.dev/badge/commands/joseairosa/recall/rlm-status.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 | $0.00015 | $0.00748 |
| Opus 5 | $0.00008 | $0.00374 |
| Sonnet 5 | $0.00003 | $0.00150 |
| Haiku 4.5 | $0.00002 | $0.00075 |
Grade A, and why
rlm-status 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/rlm-status Command
Check the status, progress, and results of an RLM execution chain.
Usage
/rlm-status <chain_id> [--detailed]
Arguments
| Argument | Required | Description |
|---|---|---|
| chain_id | Yes | The execution chain ID |
| --detailed | No | Show full subtask details and results |
Examples
# Quick status check
/rlm-status 01HXYZ12345
# Detailed view with all subtask info
/rlm-status 01HXYZ12345 --detailed
Output (Standard)
RLM Execution Status
--------------------
Chain ID: 01HXYZ12345
Status: active
Task: Find all errors and their causes
Strategy: filter
Progress
--------
Total: 5 subtasks
Completed: 3 (60%)
In Progress: 1
Pending: 1
Failed: 0
[=====> ] 60%
Estimated remaining: ~8,000 tokens
Next Steps
----------
- Continue processing remaining subtasks
- Or call merge_results when complete
Output (Detailed)
RLM Execution Status (Detailed)
-------------------------------
Chain ID: 01HXYZ12345
Status: active
Task: Find all errors and their causes
Strategy: filter
Created: 2024-01-18 10:30:00
Estimated Tokens: 50,000
Subtasks
--------
1. [completed] Find ERROR level messages
- Tokens: 1,234
- Result: Found 47 error messages across 3 categories...
2. [completed] Find WARNING level messages
- Tokens: 890
- Result: Found 23 warnings, mostly related to...
3. [completed] Find exception stack traces
- Tokens: 2,100
- Result: Identified 12 unique exceptions...
4. [in_progress] Find failure indicators
- Tokens: 750
- Result: (processing...)
5. [pending] Summarize error patterns
- Tokens: -
- Result: (not started)
Summary
-------
Tokens Used: 4,974 / 50,000 (10% coverage)
Estimated Remaining: ~8,000 tokens
Output (Completed Chain)
RLM Execution Complete
----------------------
Chain ID: 01HXYZ12345
Status: completed
Task: Find all errors and their causes
Results
-------
Confidence: 90%
Coverage: 75% of context examined
Subtasks: 5/5 completed
Merged Result Summary:
- 47 ERROR messages found
- 23 WARNING messages
- 12 unique exceptions
- Primary root cause: Database connection timeout
- Secondary issues: Memory pressure, API rate limits
Actions
-------
- View full results: call get_merged_results
- Verify findings: call verify_answer
- Store insights: call store_memory
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 · 141 lines · 15 tokens per session scan A 65729474661a
rlm-status is a command published in the GitHub repository joseairosa/recall (176 stars, last pushed 9d ago), licensed MIT. It adds 15 tokens to every session and 748 once invoked, about $0.0001 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 2026-08-30.
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