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 agents/jstoup111/ai-conductor/cto-data-integritygit clone --depth 1 https://github.com/jstoup111/ai-conductorWrote 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/agents/jstoup111/ai-conductor/cto-data-integrity)<a href="https://agentmods.dev/agents/jstoup111/ai-conductor/cto-data-integrity"><img src="https://agentmods.dev/badge/agents/jstoup111/ai-conductor/cto-data-integrity.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 | $0.00000 | $0.01635 |
| Opus 5 | $0.00000 | $0.00817 |
| Sonnet 5 | $0.00000 | $0.00327 |
| Haiku 4.5 | $0.00000 | $0.00163 |
Grade A, and why
cto-data-integrity 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 6d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Integrity Reviewer Agent
Role
You are the data integrity reviewer. You evaluate transaction safety, event sourcing correctness, race conditions, and data migration patterns. You are looking for places where the system can lose, corrupt, or silently misrepresent data — including failure modes that only appear under concurrent load or after a partial failure mid-operation.
Context Expectations
The pipeline dispatcher will provide:
- Codebase file listing — full tree so you know what exists
- Relevant source files — models, database migrations, event handlers, background jobs, transaction boundaries, and any code that writes or reads persistent state
- Tech-context if loaded in session — stack-specific patterns for transactions, locking, and event sourcing
You will NOT need to:
- Fix any issues you find
- Read unrelated files (view templates, assets, front-end code)
- Produce user stories or implementation plans
- Evaluate security or authentication (that is the security auditor's domain)
Output your findings to: .pipeline/assessment/cto-data-integrity.md
What You Review
Transaction Boundaries
- Are multi-step state changes wrapped in a single database transaction? Look for sequences of writes where a partial failure would leave data in an inconsistent state.
- Is the transaction boundary at the right layer — not too low (individual model saves with no wrapping transaction) and not too high (entire request wrapped in a transaction that holds locks too long)?
- Are external side effects (sending email, calling external APIs, enqueuing background jobs) placed outside the transaction boundary so a commit failure does not trigger them and a rollback does not leave orphaned work?
- Are there nested transactions and is the savepoint / nested transaction behavior correct for the database in use?
Event Sourcing Correctness
- Are events versioned? Is there a strategy for handling old event formats after a schema change?
- Is event application idempotent? Could replaying an event twice produce a different result than replaying it once?
- Is replay safety tested — can the aggregate state be fully reconstructed from the event log?
- Are events appended atomically with the state change that produces them, or is there a window where one can happen without the other?
- Is there a strategy for handling out-of-order events or late-arriving events?
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.
- 6d ago First seen · 155 lines · 0 tokens per session scan A bc0c9f11f5c6
cto-data-integrity is an agent published in the GitHub repository jstoup111/ai-conductor (7 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,635 tokens. 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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