Pydantic AI is a typed Python SDK for building AI agents that can use different language models and interfaces, including voice, image generation, and embeddings. Developers use it for applications ranging from structured data extraction to long-running multi-agent work. The catalogue entries provide workflows and configuration for its coding-agent and harness features.
Borrowing it
Nothing to install: this file belongs to pydantic/pydantic-ai. 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/pydantic/pydantic-ai/main/.agents/skills/file-followup-issue/SKILL.mdgit clone --depth 1 https://github.com/pydantic/pydantic-aiWrote 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/skills/pydantic/pydantic-ai/file-followup-issue)<a href="https://agentmods.dev/skills/pydantic/pydantic-ai/file-followup-issue"><img src="https://agentmods.dev/badge/skills/pydantic/pydantic-ai/file-followup-issue/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/skills/pydantic/pydantic-ai/file-followup-issue"><img src="https://agentmods.dev/badge/skills/pydantic/pydantic-ai/file-followup-issue.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 | $0.00106 | $0.01108 |
| Opus 5.5 | $0.00042 | $0.00443 |
| Sonnet 5.5 | $0.00021 | $0.00222 |
| Haiku 4.5 | $0.00011 | $0.00111 |
Grade A, and why
file-followup-issue 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 yesterday.
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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
File a follow-up issue
You discovered work that is real and worth doing, but doesn't belong in the current PR. Park it as a GitHub issue with enough context that a future session can pick it up cold and open its own PR — then get back to the current PR without touching it.
Gate — all three must hold
Only file an issue when all are true:
- The current PR is complete and stable — it closes its original issue; this discovery is not needed for that.
- The discovery is real and net-positive — a genuine bug or improvement, not a nitpick.
- It's non-trivial and out of scope — fixing it here would add its own design decisions, carry unresolved uncertainty, or widen the diff's blast radius past what the issue needed.
If a gate fails, do the alternative and stop — don't file:
- Trivial and in-scope → just fix it in this PR.
- In-scope but larger → it belongs in this PR's plan, not a new issue.
- Not actually a real problem → drop it (or, if it's a review thread, dismiss it).
Steps
-
Dedup. Search for an existing issue before creating:
gh issue list --state all --search "<3-5 distinctive keywords>" --limit 20If a clear match exists, link to it instead of creating a duplicate — and skip to step 4 (log) referencing the existing issue.
-
Confirm before creating (outward action). Show the user the drafted title + body and get a yes.
-
Create with the template below: Both title and body quote code and reviewer text, where
$(...)and backticks would be expanded by the shell beforeghever runs. Write each to its own file with your editor tool, then load the title throughcat— a shell variable's contents are not reparsed for substitution:title=$(cat <path to the title file you wrote>) gh issue create --title "$title" --body-file <path to the body file you wrote>Use the ownership shortcut only when the acting account can assign issues and apply repository labels. If a maintainer will tackle the follow-up directly or soon, use
--assignee <maintainer-login> --label pydanty:skip. This includes an AICA acting for that maintainer. Assign the maintainer who will own the work. The label prevents Pydanty from running triage orretry-pron the issue.
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.
- yesterday First seen · 100 lines · 106 tokens per session scan A 2881f2ff1b21
file-followup-issue is a skill published in the GitHub repository pydantic/pydantic-ai (20,771 stars, last pushed today), licensed MIT. It adds 106 tokens to every session and 1,108 once invoked, about $0.0004 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 2026-10-21.
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github-workflow
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github-multi-repo
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agent-release-manager
Agent skill for release-manager - invoke with $agent-release-manager.