Borrowing it
Nothing to install: this file belongs to quickcall-dev/blackbox. 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/quickcall-dev/blackbox/main/AGENTS.mdgit clone --depth 1 https://github.com/quickcall-dev/blackboxWrote 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/instructions/quickcall-dev/blackbox/agents-md)<a href="https://agentmods.dev/instructions/quickcall-dev/blackbox/agents-md"><img src="https://agentmods.dev/badge/instructions/quickcall-dev/blackbox/agents-md/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/instructions/quickcall-dev/blackbox/agents-md"><img src="https://agentmods.dev/badge/instructions/quickcall-dev/blackbox/agents-md.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 | $0.00641 | $0.00641 |
| Opus 5.5 | $0.00256 | $0.00256 |
| Sonnet 5.5 | $0.00128 | $0.00128 |
| Haiku 4.5 | $0.00064 | $0.00064 |
Grade A, and why
blackbox AGENTS.md 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 2mo 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blackbox – Agent Guide
What this repo is
Blackbox is the analysis engine inside QuickCall. It takes raw AI coding session traces (JSONL), runs a multi-stage LLM pipeline to find root causes, recurring failures, and anti-patterns, then feeds that back so future agent sessions improve.
How to run
uv sync --extra dev
uv run uvicorn src.main:app --host 0.0.0.0 --port 8000
How to test
uv run pytest # all tests
uv run pytest tests/test_api.py -x # just API tests, stop on first failure
Key files to know
| File | What it does |
|---|---|
src/main.py |
FastAPI app, routes, file upload, source detection, normalization dispatch |
src/config.py |
Settings from env/.env |
src/models.py |
Pydantic response models |
src/pipeline/orchestrator.py |
Pipeline class — runs P0–P6 stages in order |
src/pipeline/annotator.py |
Annotates raw messages with tool calls, edits, thinking blocks |
src/pipeline/context_builder.py |
Builds context windows around trigger turns |
src/pipeline/dedup.py |
Deduplicates findings by similarity threshold |
src/classify/runner.py |
Classification runner — labels user messages via LLM |
src/classify/prompts.py |
Classification system prompt + JSON schema |
src/rca/prompts.py |
All analysis prompts and JSON schemas (RCA, behavior, cluster, convention) |
src/normalizer/unified.py |
NormalizedMessage — the universal format all sources map to |
src/llm/client.py |
Async LLM client (OpenAI-compatible API) |
src/storage/run_store.py |
In-memory store for run state and stage outputs |
Architecture
See docs/architecture.md for full Mermaid diagram, file structure, data flow, and pipeline stage details.
How to add a new source format
- Add transform in
src/normalizer/<source>_transform.py - Add
normalize_<source>()function returninglist[NormalizedMessage] - Import and wire into
_normalize_file()insrc/main.py - Add detection heuristics in
_detect_source()insrc/main.py
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.
- 2mo ago First seen · 57 lines · 641 tokens per session scan A 06c6bb39f24c
blackbox AGENTS.md is an instructions file published in the GitHub repository quickcall-dev/blackbox (3 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 641 tokens to every session, about $0.0026 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.
blackbox AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| blackbox AGENTS.mdquickcall-dev/blackbox | Instructions file | 3 | 5mo ago | Apache-2.0 | A | 641 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| vscode model-prompts.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 2,022 | GitHub Copilot |