Borrowing it
Nothing to install: this file belongs to mayai-it/bandiradar. 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/mayai-it/bandiradar/main/CLAUDE.mdgit clone --depth 1 https://github.com/mayai-it/bandiradarWrote 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/mayai-it/bandiradar/claude-md)<a href="https://agentmods.dev/instructions/mayai-it/bandiradar/claude-md"><img src="https://agentmods.dev/badge/instructions/mayai-it/bandiradar/claude-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/mayai-it/bandiradar/claude-md"><img src="https://agentmods.dev/badge/instructions/mayai-it/bandiradar/claude-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 | $0.07415 | $0.07415 |
| Opus 5 | $0.03707 | $0.03707 |
| Sonnet 5 | $0.01483 | $0.01483 |
| Haiku 4.5 | $0.00741 | $0.00741 |
Grade A, and why
bandiradar CLAUDE.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 8d 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 — 403 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — bandiradar (open core)
Internal status, roadmap and strategy live in ROADMAP.local.md (gitignored, local only — read it first if present).
Project memory for coding agents. Read this fully before editing. The deep design
lives in ARCHITECTURE.md; this file is the operational contract.
One-liner
Open-source engine that monitors Italian public funding opportunities (tenders,
grants, incentives), normalizes them into one canonical Opportunity model, and
ranks them against a company Profile with a two-stage matcher.
What this repo IS / IS NOT
- IS (open, MIT): engine,
Sourceframework, reference adapters (ANAC, later incentivi.gov.it), two-stage matcher, CLI, MCP server. - IS NOT (lives in private
bandiradar-pro): web dashboard, premium/regional adapters, delivery channels (WhatsApp/email/alerts), multi-tenant, hosting. - Boundary rule: single-user/local = here. Managed/multi-client/delivery = pro.
- Never add dashboard, paid, or delivery-channel code to this repo.
Architecture map (module → responsibility)
src/bandiradar/
models.py # pydantic: Opportunity, RawDoc, Profile, Match. THE contract.
sources/
base.py # Source Protocol + registry
anac.py # ANAC/PNCP (OCDS) historical adapter + fixture
anac_pvl.py # ANAC PVL — OPEN tenders, live, no-creds + fixture
heal.py # LLM crawl-recipe healer (re-derives a drifted recipe)
llm_scraper.py # reusable LLM HTML extractor; re-exports the crawl spine
wordpress.py # reusable WP-REST base (lazio, sicilia configs)
plone.py # reusable Plone `Bando` base (emilia_romagna config)
sicilia.py # EuroInfoSicilia FESR/FSC (WP base + categories filter)
emilia_romagna.py # ER Politiche territoriali (Plone Bando)
trentino.py # Prov. Trento FEASR — CKAN open-data CSV adapter
veneto.py # Veneto SIU — LlmScraperSource (landing, HTML regex-recipe heal)
piemonte.py # Piemonte Drupal — LlmScraperSource (Views, HTML regex-recipe heal)
puglia.py # Puglia PR 21-27 — LlmScraperSource (Liferay fragment, badge; detect-only)
sardegna.py # Sardegna Impresa — LlmScraperSource (Views, HTML regex-recipe heal)
fvg.py # FVG bandi module — LlmScraperSource (contributi filter in regex; recipe heal; relay in CI)
campania.py # Sviluppo Campania — LlmScraperSource (widget anchors, title_template; recipe heal)
calabria.py # Calabria Europa — LlmScraperSource (WP-REST CPT, JSON recipe heal)
basilicata.py # Portalebandi — LlmScraperSource (WP-REST CPT, JSON recipe heal)
liguria.py # Liguria publiccompetition — LlmScraperSource (POST+CSRF fetch, regex recipe heal)
cpv.py # CPV Italian-label → 8-digit code resolver (pure, offline)
trust.py # trust spine: deterministic validation of LLM extractions (pure)
crawl.py # self-healing crawl spine (stdlib: recipes + drift + golden)
recipe_store.py # per-source CrawlRecipe overrides + golden (CONFIG, not code)
matching/
prefilter.py # Stage 1: pure deterministic filter
relevance.py # Stage 2: LLM scorer (+ offline fallback + cache)
llm.py # provider-agnostic LLM client
prompts.py # prompt templates
storage.py # SQLite store, dedupe, change detection
# + crawl_recipes + crawl_golden tables (self-healing crawl)
core.py # service layer that orchestrates the pipeline
evaluation.py # matching-quality eval: pure metrics + run over eval corpus
cli.py # Typer CLI (thin)
mcp_server.py # FastMCP server (thin)
resources.py # importlib.resources access to packaged data (below)
data/ # PACKAGED runtime data (ships in the wheel)
fixtures/ # recorded source payloads for offline tests / --sample
profiles/ # example profiles (mayai.yaml, manifattura.yaml, …)
eval/ # labelled eval set: opportunities.jsonl + gold.yaml
cpv_it.json # official EU CPV 2008 vocabulary (Italian label → code)
comuni_it.json # ISTAT comuni table (region resolution for anac_pvl)
tests/
scripts/
monitor_status.py # live-monitor STATUS.md generator (pure, offline, tested)
.github/workflows/
monitor.yml # daily self-maintaining monitor (keyless; key→LLM+healer)
Runtime data lives INSIDE the package and is reached via bandiradar.resources
(importlib.resources) — never Path(__file__).parents[...] — so --sample and the
bundled example profiles work from a pip-installed wheel, not only a checkout.
Interfaces (cli.py, mcp_server.py) are THIN — no business logic. All logic
lives in core.py, sources/, matching/, storage.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.
- 8d ago First seen · 403 lines · 7,415 tokens per session scan A 33a771b31bd6
bandiradar CLAUDE.md is an instructions file published in the GitHub repository mayai-it/bandiradar (2 stars, last pushed 2mo ago), licensed MIT. It adds 7,415 tokens to every session, about $0.0371 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.
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