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 commands/pydantic/skills/dev-sessiongit clone --depth 1 https://github.com/pydantic/skillsWhat 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 | $0.00019 | $0.01515 |
| Opus 5 | $0.00010 | $0.00758 |
| Sonnet 5 | $0.00004 | $0.00303 |
| Haiku 4.5 | $0.00002 | $0.00152 |
Grade A, and why
dev-session 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/dev-session
Start a local Logfire dev session that creates temporary credentials and injects them into your app so you can view traces in the Logfire UI.
Prerequisites
The Logfire MCP server must be connected (this plugin configures it automatically).
Workflow
Step 1: Create the dev session
Call the mcp__logfire__local_dev_session MCP tool to provision a temporary dev project and get credentials. This returns:
- Logfire SDK env vars (
LOGFIRE_TOKEN,LOGFIRE_BASE_URL) - Plain OTEL env vars (
OTEL_EXPORTER_OTLP_ENDPOINT,OTEL_EXPORTER_OTLP_HEADERS, etc.) OTEL_RESOURCE_ATTRIBUTESwith a session tag for filtering traces- A Logfire UI link to view traces
Save all returned values — you will need them in the injection step.
Step 2: Analyze the codebase
Determine how the app is run and configured by scanning for:
- Env files:
.env,.env.local,.env.development - Container orchestration:
docker-compose.yml/docker-compose.yaml, Kubernetes manifests (k8s/,deploy/,*.yamlwithkind: Deployment) - Dev tools:
Tiltfile(Tilt),skaffold.yaml(Skaffold),devcontainer.json/.devcontainer/ - Process managers:
Procfile(foreman/honcho) - Build/run targets:
Makefile,justfilewith dev/run targets - Deployment config:
fly.toml,helmfile.yaml, Helmvalues.yaml - Framework conventions: Next.js uses
.env.local, Python apps typically use.env
Also check whether Logfire or OpenTelemetry is already instrumented:
- Look for
logfirein Python dependencies,@pydantic/logfire-nodeorlogfireinpackage.json,logfireinCargo.toml - Look for OpenTelemetry SDK imports without Logfire
- If the app is not instrumented at all, tell the user and suggest running
/instrumentfirst. The dev session credentials will still work once instrumentation is added, so continue with injection.
Step 3: Inject credentials
Choose the best injection method based on what you found. Prefer methods that support hot reload so the user doesn't have to restart manually.
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 · 117 lines · 19 tokens per session scan A 09399b7e82f2
dev-session is a command published in the GitHub repository pydantic/skills (127 stars, last pushed 2d ago), licensed MIT. It adds 19 tokens to every session and 1,515 once invoked, about $0.0001 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.