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/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/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/ololand-ai/ololand-plugins/dd-correct"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/dd-correct.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 | $0.00050 | $0.00386 |
| Opus 5.5 | $0.00020 | $0.00154 |
| Sonnet 5.5 | $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 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.
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.
- 1mo 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 3d ago), licensed Apache-2.0. It adds 50 tokens to every session and 386 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.
speckit.bug.test
Validate that a previously fixed bug is resolved and record the verification report.