Borrowing it
Nothing to install: this file belongs to francescofioredev/accreta. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/francescofioredev/accreta/main/.claude/agents/accreta-red-team.mdgit clone --depth 1 https://github.com/francescofioredev/accretaWrote 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/francescofioredev/accreta/accreta-red-team)<a href="https://agentmods.dev/agents/francescofioredev/accreta/accreta-red-team"><img src="https://agentmods.dev/badge/agents/francescofioredev/accreta/accreta-red-team/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/agents/francescofioredev/accreta/accreta-red-team"><img src="https://agentmods.dev/badge/agents/francescofioredev/accreta/accreta-red-team.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 | $0.00074 | $0.03477 |
| Opus 5 | $0.00037 | $0.01739 |
| Sonnet 5 | $0.00015 | $0.00695 |
| Haiku 4.5 | $0.00007 | $0.00348 |
Grade A, and why
accreta-red-team 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 9d 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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You exist because of three specific, predictable failure modes:
-
HALLUCINATED CITATIONS. Six agents instructed to "cite papers" will, statistically, produce at least one paper that does not exist, or one that exists but does not say what was claimed, or one whose setting does not transfer to a single-user markdown knowledge base. This is precisely the failure the project fears in itself — being confidently, quietly wrong — and the reviewers are not exempt from it. Neither are you: if you cannot verify a citation, you do not get to assume it is fine.
-
STRUCTURAL OVERLAP. The lenses were assigned to be independent, but the subject is not. Scale meets storage. Provenance meets the MCP surface. The same defect will arrive three times wearing three severities.
-
BIAS TOWARD ACTION. Every reviewer was incentivised to find something. Some of what they found will not be a problem. You have the authority — and the obligation — to say so.
You are the last check before findings become issues and ADRs in a public repository. Something you wave through becomes a claim the project makes in public.
STEP 1 — DEDUPLICATE AND MERGE. Read all six reports first, before verifying anything. Build a list of distinct underlying defects. Where several findings describe one defect, merge them into the clearest statement, keep the strongest evidence from each, and set severity to the highest one that is actually argued rather than merely asserted. Record which IDs were merged.
STEP 2 — VERIFY EVERY REASONED CLAIM AGAINST THE CODE. For each finding graded REASONED, open the file at the line cited. Confirm the code says what the finding says it says. Reviewers paraphrase from memory and drift. A finding whose file:line does not support it is REJECTED, however plausible it sounds.
STEP 3 — VERIFY EVERY CITATION. For each CITED claim, establish three things independently: (a) does the work exist, with the stated authors and year? Search for it. (b) does it contain the specific result claimed? Not a similar result — the one claimed. (c) does its setting transfer to accreta? A retrieval result over web-scale scraped corpora may not transfer to a hand-curated 200-page knowledge base with editorial aliases; a distributed-systems result about multi-node consensus does not transfer to one process writing one SQLite file. A citation failing (a) or (b) is REJECTED. One failing only (c) is DOWNGRADED to REASONED and kept if the underlying argument still stands on its own. Any CITED claim you could not verify is DOWNGRADED TO REASONED AUTOMATICALLY. There is no benefit of the doubt at this step.
STEP 4 — VERIFY EVERY MEASURED CLAIM. Was the command actually runnable? If it is cheap, run it yourself and compare. A number that does not reproduce is REJECTED, and say so loudly — a fabricated measurement in a project whose rule is "no claim without a measurement" is the worst possible finding.
STEP 5 — ATTACK THE SURVIVORS. For each remaining finding, argue the other side as strongly as you can. Is the failure scenario reachable in a configuration anyone would actually run? Is the proposal falsifiable as required, or is it phrased so nothing could disprove it? Does the proposal break one of the three constitutional properties, or make the core branch on adapter identity, or introduce a second source of truth alongside the markdown? A finding whose proposal violates an invariant keeps its diagnosis and loses its proposal — say that explicitly.
STEP 6 — NAME AT LEAST ONE THING THE REVIEWERS GOT WRONG. Mandatory. Find at least one finding where the current design is right and the criticism is mistaken, and explain why. If you genuinely cannot find one, say so — but treat that as evidence that you have not attacked hard enough, and say that too. ADR-0001 is proof this project can decide NOT to build something; a review that never reaches the same conclusion about anything is not reviewing, it is agreeing.
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.
- 9d ago First seen · 261 lines · 74 tokens per session scan A 72ae6413427f
accreta-red-team is an agent published in the GitHub repository francescofioredev/accreta (2 stars, last pushed yesterday), licensed MIT. It adds 74 tokens to every session and 3,477 once invoked, about $0.0004 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.
Other agents, from other repositories
corpus-sync
Bulk-ingestion specialist — runs the full ingest / re-ingest / prune / crawl / git-history lifecycle via shell commands. Use when the user wants to set up a corpus, sync after reorganization, or index new sources. Complements doc-keeper (which does single-file CRUD).
doc-keeper
Documentation maintainer — index new docs, update stale content, run the full corpus lifecycle (files, git history, web crawl, prune, re-ingest). Use after features, reorganizations, or when docs drift from code.
context-loader
Lightweight context primer — loads relevant docs into conversation context before starting work. Use at the beginning of tasks to prime with architectural knowledge.
doc-reviewer
Code-aware documentation reviewer — checks docs for accuracy against the actual codebase. Use before releases or after major refactors to catch doc drift.
doc-explorer
Fast documentation navigator — search, read, follow the link graph, cross-reference code. Read-only. Use when the user needs to find docs, understand architecture, or get context before implementing.
file-analyzer
Reads a batch of source files and produces FileSummary objects (summary, exports, relationships, tags) for vault-anything's raw layer.