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/qoe-analysisgit 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/qoe-analysis)<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/qoe-analysis"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/qoe-analysis.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 5.1 | $0.00048 | $0.00650 |
| Opus 5 | $0.00024 | $0.00325 |
| Sonnet 5 | $0.00010 | $0.00130 |
| Haiku 4.5 | $0.00005 | $0.00065 |
Grade A, and why
qoe-analysis 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 5d 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QoE Analysis
Run the deal-scoped Quality of Earnings workbench. The backend auto-hydrates from the latest financial snapshot when explicit data is not provided, while still accepting overrides for replay or power-user workflows.
Usage
/qoe-analysis <deal_id> [latest|run]
Arguments
deal_id(required) - The deal to analyze.mode(optional) -latestto inspect the cached result;runto create a fresh analysis. Default:latest, then run if no result exists.
Execution
- Call
get_latest_qoe_analysis(deal_id). - If there is no cached result, or the user asks to rerun, call
run_qoe_analysis(deal_id). - If the user supplied structured overrides, pass them through to
run_qoe_analysis:revenue_items,expense_items,financial_data,transactions,adjustments,reported_ebitda,revenue_data, andworking_capital_data. - Use the returned
view_urlfor the web app handoff.
Cross-document conflict scan (optional)
QoE findings are only as good as the documents agree with each other. When the user asks to "find contradictions", "check the documents against each other", or is prepping a data-room quality read, run the cross-document conflict detector:
- Call
run_conflict_detection(deal_id). This dispatches the Deal Document Conflict Detector over the cross-doc reconciliation engines, surfacing conflicts across financials, dates, entities, and terms. It returns atask_idand dual-writes a replayableagent_runsrow plus aconflict_reportartifact. - Poll
check_task_status(task_id)until complete (it runs async). - Fold the returned conflicts into the QoE read as evidence gaps or blockers — a management figure that contradicts the CPA financials is a QoE concern, not a footnote. Cite the two conflicting documents for each finding.
This is the all-in-one equivalent of the standalone ololand-forensic-qoe plugin's /conflicts command.
Output
Render:
- QoE verdict - clean / watch / concern / blocker, based on the returned risk and adjustment profile.
- EBITDA bridge - reported EBITDA -> normalized EBITDA, with adjustment classes and dollar impacts.
- Revenue quality - concentration, cut-off, recurring/non-recurring indicators, and any source gaps.
- Working capital - DSO/DPO/DIO and normalization flags.
- Evidence gaps - data classes that prevented stronger conclusions.
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.
- 5d ago First seen · 52 lines · 48 tokens per session scan A 80b29c425625
qoe-analysis is a command published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 48 tokens to every session and 650 once invoked, about $0.0002 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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