Borrowing it
Nothing to install: this file belongs to flnzba/flnzba.github.io. 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/flnzba/flnzba.github.io/main/AGENTS.mdgit clone --depth 1 https://github.com/flnzba/flnzba.github.ioWrote 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/flnzba/flnzba.github.io/agents-md)<a href="https://agentmods.dev/instructions/flnzba/flnzba.github.io/agents-md"><img src="https://agentmods.dev/badge/instructions/flnzba/flnzba.github.io/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/flnzba/flnzba.github.io/agents-md"><img src="https://agentmods.dev/badge/instructions/flnzba/flnzba.github.io/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 | $0.00879 | $0.00879 |
| Opus 5.5 | $0.00352 | $0.00352 |
| Sonnet 5.5 | $0.00176 | $0.00176 |
| Haiku 4.5 | $0.00088 | $0.00088 |
Grade A, and why
flnzba.github.io 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 25d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engineering Agent Instructions
Applies to every agent session here and in template-derived repositories.
Before deciding
- Inspect current code, tree, and effective runtime/config. Stale or unverified artifacts cannot override observed state or user-approved requirements.
- Query the CodeGraph MCP index first for structure, symbols, callers, and impact; explore by hand only what the index does not answer. The index persists across sessions — do not re-derive what it already knows.
- Use the
software-engineeringskill for every substantive task: requirements, architecture, implementation, debugging, or review. It loads automatically; never wait for a slash command. - Derive before you ask. The repo, git history, the user's own sites, package registries, vendor docs and installed CLIs answer most factual questions. Before calling an external dependency blocking, check whether its CLI is authenticated and whether the account already holds what you need.
While working
- Prefer the smallest correct change. Reuse native and existing capabilities before adding code, configuration, or dependencies. A datastore nothing queries, a service nothing calls, an endpoint nothing hits: build each when something needs it, so it never becomes the scope you delete later.
- Keep requirements and product decisions in the main conversation. Ask only questions whose answers change what you will build.
- Resolve root causes. Never suppress, work around, or defer an error to keep moving.
- Edit canonical sources; regenerate and verify derived outputs. Never hand-edit copies or assume config is effective.
- Re-scan shared state before mutations. Never revert, overwrite, or clean up work you did not make. Keep secrets out of commits, logs, and tool output.
- Follow the repo-wide service architecture standard (see the
software-engineeringskill's architecture reference): DTOs at API boundaries, data access behind DAOs/repositories, services communicate only through published APIs. Use repository-managed runtimes and commands; Python runs only through the project venv or a managed runner. Keep hermetic checks independent of ambient credentials and network. - Configuration is centralized (see the skill's platform reference): committed non-secret env bases plus one gitignored secrets file whose keys are all listed in a committed example; no per-service env files, no environment literals in code.
- Infrastructure keeps three tiers (platform reference): leaf modules → one root stack → thin per-environment roots. Topology is declared data, secrets are injected, and generated config carries a drift check.
- Delegate independent read-heavy work (exploration, research, review) to subagents; never run concurrent editing agents. Independently verify their claims. The current user request outranks stale hook or TODO work.
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.
- 25d ago First seen · 79 lines · 879 tokens per session scan A 738d7ab6c783
flnzba.github.io AGENTS.md is an instructions file published in the GitHub repository flnzba/flnzba.github.io (0 stars, last pushed 2mo ago), licensed MIT. It adds 879 tokens to every session, about $0.0035 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 2026-10-02.
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