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/ololand-ai/ololand-plugins/dd-correctgit clone --depth 1 https://github.com/ololand-ai/ololand-pluginsWrote 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/ololand-ai/ololand-plugins/dd-correct)<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/dd-correct"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/dd-correct.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 | $0.00050 | $0.00386 |
| Opus 5 | $0.00025 | $0.00193 |
| Sonnet 5 | $0.00010 | $0.00077 |
| Haiku 4.5 | $0.00005 | $0.00039 |
Grade A, and why
dd-correct 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 3d 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.
What it actually says
/dd-correct
You are submitting a claim-level correction on an OloLand agent output via the Cowork plugin.
Required inputs
Ask the user for these if any are missing:
- run_id — the OloLand agent run that produced the output. Format: starts with
run-or is a UUID. - span_id — the agent_span ID for the specific LLM call that emitted the claim. Visible in the OloLand admin replay UI; ask the user to paste it.
- claim_id — the inline
[N]marker number on the claim being flagged. - claim_text — the verbatim text of the flagged claim (so the correction is human-readable later).
- delta_type — one of:
factual,missing_evidence,scope_drift,tone,citation_wrong,other. If unclear, ask the user to pick. - deal_id — the OloLand deal this output is about.
Optional:
- correction_text — what the claim should say instead.
- severity —
low,medium, orhigh. Defaultmedium. - citation_doc — name of the source document being miscited.
- citation_page — page number being miscited.
Action
Call the OloLand MCP tool submit_agent_claim_correction with the collected fields. The tool stamps surface: cowork automatically.
After success, confirm to the user with the returned correction id and a one-line summary of what was flagged.
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.
- 3d ago First seen · 31 lines · 50 tokens per session scan A 4a2ae4e60b7c
dd-correct is a command published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 6d ago), licensed Apache-2.0. It adds 50 tokens to every session and 386 once invoked, about $0.0003 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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