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/conorbronsdon/agent-context-os/dream-applygit clone --depth 1 https://github.com/conorbronsdon/agent-context-osWrote 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/conorbronsdon/agent-context-os/dream-apply)<a href="https://agentmods.dev/commands/conorbronsdon/agent-context-os/dream-apply"><img src="https://agentmods.dev/badge/commands/conorbronsdon/agent-context-os/dream-apply.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 | $0.00020 | $0.03273 |
| Opus 5 | $0.00010 | $0.01636 |
| Sonnet 5 | $0.00004 | $0.00655 |
| Haiku 4.5 | $0.00002 | $0.00327 |
Grade A, and why
dream-apply scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/dream-apply — review + apply a curator pass
Substrate background: docs/dream-architecture.md.
Usage
/dream-apply {ISO-timestamp}
/dream-apply latest # auto-resolves to most recent .dreams/ subdir
Steps
1. Resolve the dream dir
Run the executable validator before reading or applying any artifact:
python3 scripts/dream/validate-memory.py artifact "${ARGUMENTS:-latest}"
Parse the returned JSON. Set MEMORY_DIR from memory_dir, TS from timestamp, and the dream dir from dream_dir. The helper rejects malformed timestamps, path traversal, absolute or control-character arguments, symlinked artifact components, missing proposals.json/REPORT.md, malformed or colliding proposal schemas, unknown/roadmap actions, empty evidence, unsafe control-file targets, and any proposal filename outside the validated memory root. It also requires the memory repository to be clean before review; stop so any host auto-memory change can be reviewed or snapshotted separately.
Do not create or guess a memory directory when a check fails. Stop and direct the user to docs/auto-memory.md.
If $ARGUMENTS is latest or empty, the helper resolves the most recent valid dream artifact by name. Do not reimplement timestamp/path selection in prose.
2. Load the proposal artifact
Read the validated $dream_dir/proposals.json and $dream_dir/REPORT.md. If either becomes missing or changes after validation, rerun the helper and stop on any error.
3. Show the report header
Print the top of REPORT.md (header + counts). Don't dump the whole thing — the user already has it if they want the full text.
4. Walk each proposal
For each proposals[i]:
a. Print a header, then the fields relevant to the action:
─── Proposal {id} ({i+1}/{N}) ───
Action: {action} Confidence: {confidence}
Reasoning: {reasoning}
Evidence:
- {evidence[0]}
- {evidence[1]}
modify(content):Target: {target}thenCurrent:/Proposed:excerpts.archive:Target: {target}then the one-line archive reason.merge(structural):Absorb: {targets}→Survivor: {survivor}(net index lines: {net_index_lines}), then themerged_bodyand theindex_changes.split(structural):Target: {target}→Into: {result_files[*].name}, then each child'spurpose+index_lineand itsbody.add/flag: target + proposed content (add) or the flagged concern (flag).
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.
- today Changed 4d92d3b919ec
- 5d ago First seen · 188 lines · 20 tokens per session scan A cb10230540d9
dream-apply is a command published in the GitHub repository conorbronsdon/agent-context-os (22 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 3,273 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.
Other commands, from other repositories
cm-doctor
Print the resolved StoreContext (native/canonical/control-plane paths, enrollment, registry health).
generate-docs
Generates a Rust-scoped symbol inventory to assist agents in understanding the public API surface of the workspace.
extensions
Show what the connected context expects to reach, and whether this machine provides it.
list
List the NeatContext contexts you can connect.
ctx
Experimental integration for ctx in Cursor.
bye
../../workflows/bye.md.