Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/runpod/flash/claude-mdgit clone --depth 1 https://github.com/runpod/flashWhat 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 | $0.02865 | $0.02865 |
| Opus 5 | $0.01432 | $0.01432 |
| Sonnet 5 | $0.00573 | $0.00573 |
| Haiku 4.5 | $0.00286 | $0.00286 |
Grade A, and why
flash 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 2d 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 — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flash (runpod-flash)
Auto-generated by /analyze-repos on 2026-02-22. Manual edits will be overwritten on next analysis.
Project Overview
runpod-flash (v1.3.0, PyPI: runpod-flash, MIT, Python >=3.10 <3.13). Python SDK for distributed inference and serving on Runpod serverless. Provides @remote decorator, CLI (flash init/run/build/deploy), runtime for serialization, endpoint provisioning, cross-endpoint routing, and load-balanced HTTP serving.
Package: runpod_flash (src layout). Key deps: cloudpickle, runpod, pydantic>=2.0, rich>=14.0, typer>=0.12.
Architecture
Key Abstractions
- ServerlessResource (
src/runpod_flash/core/resources/serverless.py:93) -- Base Pydantic model for all serverless endpoint configs. Extends DeployableResource with config hashing, drift detection, deployment lifecycle. - ResourceManager (
src/runpod_flash/core/resources/resource_manager.py:22) -- Singleton managing dynamic provisioning, persistence, config drift detection, concurrent deployment locking. - ServiceRegistry (
src/runpod_flash/runtime/service_registry.py:21) -- Runtime service discovery for cross-endpoint function routing. Loadsflash_manifest.json, queries State Manager. - remote() decorator (
src/runpod_flash/client.py:48) -- Primary public API. Three modes: stub creation, local execution in deployed env, LB route handler. - stub_resource() singledispatch (
src/runpod_flash/stubs/registry.py:22) -- Polymorphic stub factory. Dispatches on resource type to create execution stubs.
Entry Points
- CLI:
src/runpod_flash/cli/main.py:30(flash = runpod_flash.cli.main:app). Commands:init,run,build,deploy,env,app,undeploy - Module entry:
src/runpod_flash/cli/main.py:89 - Programmatic:
src/runpod_flash/__init__.pyexportsremote,LiveServerless, etc.
Module Structure
src/runpod_flash/
__init__.py # Package root; lazy imports, dotenv, logging
client.py # @remote decorator (3 modes: stub/local/LB)
config.py # FlashPaths NamedTuple
execute_class.py # RemoteClassWrapper, class serialization
logger.py # SensitiveDataFilter, setup_logging()
cli/ # CLI layer (Typer-based)
main.py # CLI app definition
commands/
init.py # flash init
run.py # flash run (dev server codegen + uvicorn)
build.py # flash build (artifact packaging)
deploy.py # flash deploy (build + upload + provision)
preview.py # flash deploy --preview (Docker Compose)
env.py, apps.py, undeploy.py
_run_server_helpers.py # lb_execute, make_input_model
build_utils/
scanner.py # AST-based @remote detection for API key analysis
manifest.py # flash_manifest.json generation
handler_generator.py, lb_handler_generator.py, resource_config_generator.py
utils/ # app.py, conda.py, deployment.py, formatting.py, ignore.py, skeleton.py
core/ # Core business logic
deployment.py # DeploymentOrchestrator
discovery.py # ResourceDiscovery (AST scanning)
exceptions.py, validation.py
api/runpod.py # RunpodGraphQLClient, RunpodRESTClient (899 lines)
resources/ # All resource types, ResourceManager, GPU/CPU enums, constants
utils/ # backoff, constants, file_lock, http, lru_cache, singleton, user_agent
runtime/ # Deployed runtime (runs inside workers)
service_registry.py # Cross-endpoint routing via manifest
production_wrapper.py # Production handler wrapper
lb_handler.py # Load balancer FastAPI handler
circuit_breaker.py, models.py, config.py, context.py
serialization.py, state_manager_client.py
resource_provisioner.py, retry_manager.py, metrics.py, reliability_config.py
stubs/ # Execution dispatch
registry.py # singledispatch stub factory
live_serverless.py, serverless.py, load_balancer_sls.py, dependency_resolver.py
protos/ # FunctionRequest dataclass, protobuf definitions
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.
- 2d ago First seen · 256 lines · 2,865 tokens per session scan A 577d4abd586d
flash CLAUDE.md is an instructions file published in the GitHub repository runpod/flash (182 stars, last pushed 5d ago), licensed MIT. It adds 2,865 tokens to every session, about $0.0143 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 2026-08-30.
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