Borrowing it
Nothing to install: this file belongs to agent-receipts/obsigna. 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/agent-receipts/obsigna/main/.github/instructions/python.instructions.mdgit clone --depth 1 https://github.com/agent-receipts/obsignaWrote 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/agent-receipts/obsigna/python)<a href="https://agentmods.dev/instructions/agent-receipts/obsigna/python"><img src="https://agentmods.dev/badge/instructions/agent-receipts/obsigna/python/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/agent-receipts/obsigna/python"><img src="https://agentmods.dev/badge/instructions/agent-receipts/obsigna/python.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 | $0.00113 | $0.00113 |
| Opus 5.5 | $0.00045 | $0.00045 |
| Sonnet 5.5 | $0.00023 | $0.00023 |
| Haiku 4.5 | $0.00011 | $0.00011 |
Grade A, and why
obsigna python.instructions.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.
What it actually says
Python SDK review guidelines
- Prefer
from __future__ import annotationsin new or heavily-typed modules. - Pydantic v2 for receipt models, frozen dataclasses for simple types.
- Use
TYPE_CHECKINGguards for type-only imports. - Ruff for lint and format (line-length 88). Flag lines exceeding this.
- Tests mirror
src/structure undertests/. Flag tests placed elsewhere. - Output must be byte-identical to the TypeScript SDK.
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 · 13 lines · 113 tokens per session scan A bb9a2b72545b
obsigna python.instructions.md is an instructions file published in the GitHub repository agent-receipts/obsigna (20 stars, last pushed today), licensed Apache-2.0. It adds 113 tokens to every session, about $0.0005 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 2026-08-30.
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