pi's full system prompt: 4 versions, 7,425 characters. Audited against AISPA.
The full text of 4
prompts is reproduced below,
7,425 characters in all, each read
instruction by instruction against the eight
AISPA dimensions.
Nothing was flagged as working against the person on
the other end.
---
description: Audit changelog entries before release
---
Audit changelog entries for all commits since the last release.
## Process
1. **Find the last release tag:**
```bash
git tag --sort=-version:refname | head -1
```
2. **List all commits since that tag:**
```bash
git log <tag>..HEAD --oneline
```
3. **Read each package's [Unreleased] section:**
- packages/ai/CHANGELOG.md
- packages/tui/CHANGELOG.md
- packages/coding-agent/CHANGELOG.md
4. **For each commit, check:**
- Skip: changelog updates, doc-only changes, release housekeeping
- Skip: changes to generated model catalogs (for example `packages/ai/src/models.generated.ts`) unless accompanied by an intentional product-facing change in non-generated source/docs.
- Determine which package(s) the commit affects (use `git show <hash> --stat`)
- Verify a changelog entry exists in the affected package(s)
- For external contributions (PRs), verify format: `Description ([#N](url) by [@user](url))`
5. **Cross-package duplication rule:**
Changes in `ai`, `agent` or `tui` that affect end users should be duplicated to `coding-agent` changelog, since coding-agent is the user-facing package that depends on them.
6. **Add New Features section after changelog fixes:**
- Insert a `### New Features` section at the start of `## [Unreleased]` in `packages/coding-agent/CHANGELOG.md`.
- Propose the top new features to the user for confirmation before writing them.
- Link to relevant docs and sections whenever possible.
7. **Report:**
- List commits with missing entries
- List entries that need cross-package duplication
- Add any missing entries directly
## Changelog Format Reference
Sections (in order):
- `### Breaking Changes` - API changes requiring migration
- `### Added` - New features
- `### Changed` - Changes to existing functionality
- `### Fixed` - Bug fixes
- `### Removed` - Removed features
Attribution:
- Internal: `Fixed foo ([#123](https://github.com/earendil-works/pi-mono/issues/123))`
- External: `Added bar ([#456](https://github.com/earendil-works/pi-mono/pull/456) by [@user](https://github.com/user))`
---
description: Analyze GitHub issues (bugs or feature requests)
argument-hint: "<issue>"
---
Analyze GitHub issue(s): $ARGUMENTS
For each issue:
1. Add the `inprogress` label to the issue via GitHub CLI and assign the issue to the local `gh` user before analysis starts. If either action fails, report that explicitly and continue.
2. Read the issue in full, including all comments and linked issues/PRs.
3. Do not trust analysis written in the issue. Independently verify behavior and derive your own analysis from the code and execution path.
4. **For bugs**:
- Ignore any root cause analysis in the issue (likely wrong)
- Read all related code files in full (no truncation)
- Trace the code path and identify the actual root cause
- Propose a fix
5. **For feature requests**:
- Do not trust implementation proposals in the issue without verification
- Read all related code files in full (no truncation)
- Propose the most concise implementation approach
- List affected files and changes needed
Do NOT implement unless explicitly asked. Analyze and propose only.
---
description: Review PRs from URLs with structured issue and code analysis
argument-hint: "<PR-URL>"
---
You are given one or more GitHub PR URLs: $@
For each PR URL, do the following in order:
1. Add the `inprogress` label to the PR via GitHub CLI before analysis starts. If adding the label fails, report that explicitly and continue.
2. Read the PR page in full. Include description, all comments, all commits, and all changed files.
3. Identify any linked issues referenced in the PR body, comments, commit messages, or cross links. Read each issue in full, including all comments.
4. Analyze the PR diff without checking out or switching to the PR branch. Use `gh pr diff`, `gh pr view`, `gh api`, and local main-branch files; if PR file contents are needed, use fetched refs with `git show <ref>:<path>` or temporary files. Read all relevant code files in full with no truncation and compare against the diff. Do not fetch PR file blobs unless a file is missing on main or the diff context is insufficient. Include related code paths that are not in the diff but are required to validate behavior.
5. Do not check for a changelog entry. Per CONTRIBUTING.md, contributor PRs must not edit `CHANGELOG.md` — the maintainer adds the entry when merging.
6. Check if packages/coding-agent/README.md, packages/coding-agent/docs/*.md, packages/coding-agent/examples/**/*.md require modification. This is usually the case when existing features have been changed, or new features have been added.
7. Provide a structured review with these sections:
- What it does: one short paragraph describing the change and its intent.
- Good: solid choices or improvements.
- Bad: concrete issues, regressions, missing tests, or risks.
- Ugly: subtle or high impact problems.
- Tests: what is covered, what is missing, and whether existing tests are adequate.
- Open questions for you: only things blocking a merge decision that need the user's input. Omit the section entirely if there are none.
Output format per PR:
PR: <url>
What it does:
- ...
Good:
- ...
Bad:
- ...
Ugly:
- ...
Tests:
- ...
Open questions for you:
- ...
If no issues are found, say so under Bad and Ugly.
---
description: Finish the current task end-to-end with changelog, commit, and push
argument-hint: "[instructions]"
---
Wrap it.
Additional instructions: $ARGUMENTS
Determine context from the conversation history first.
Rules for context detection:
- If the conversation already mentions a GitHub issue or PR, use that existing context.
- If the work came from `/is` or `/pr`, assume the issue or PR context is already known from the conversation and from the analysis work already done.
- If there is no GitHub issue or PR in the conversation history, treat this as non-GitHub work.
Unless I explicitly override something in this request, do the following in order:
1. Add or update the relevant package changelog entry under `## [Unreleased]` using the repo changelog rules.
2. If this task is tied to a GitHub issue or PR and a final issue or PR comment has not already been posted in this session, draft it in my tone, preview it, and post exactly one final comment. The comment must end with this exact standalone disclaimer line, with no variations:
```text
This comment is AI-generated by `/wr`
```
3. Commit only files you changed in this session.
4. If this task is tied to exactly one GitHub issue, include `closes #<issue>` in the commit message. If it is tied to multiple issues, stop and ask which one to use. If it is not tied to any issue, do not include `closes #` or `fixes #` in the commit message.
5. Check the current git branch. If it is not `main`, stop and ask what to do. Do not push from another branch unless I explicitly say so.
6. Push the current branch.
Constraints:
- Never stage unrelated files.
- Never use `git add .` or `git add -A`.
- Run required checks before committing if code changed.
- Do not open a PR unless I explicitly ask.
- If this is not GitHub issue or PR work, do not post a GitHub comment.
- If a final issue or PR comment was already posted in this session, do not post another one unless I explicitly ask.
Questions about pi's system prompt
Does pi's system prompt contain instructions that work against the user?
No. Nothing in pi's system prompt was flagged as working against the person the product is talking to. That is a clean result across all eight AISPA dimensions, not an absence of checking — the full text was read instruction by instruction.
How long is pi's system prompt?
7,425 characters across 4 prompts on this page. For comparison, the median system prompt in this index runs about 5,400 characters, so length varies by more than two orders of magnitude between products.
How many versions of pi's system prompt are on record?
4. Older releases are kept rather than replaced, so the wording of a given version stays readable after the product has moved on.
Where did this pi system prompt come from?
It was collected from publicly available sources and is reproduced here for transparency research, unedited. This site does not extract prompts from products itself.
How was pi's system prompt audited?
Against AISPA, an eight-dimension standard for how an instruction treats the person on the other end: identity transparency, truthfulness, privacy, tool safety, user agency, unsafe request handling, harm prevention and fairness. This audit was ai audit. The method is described in the paper behind the standard.
How this page was made
The prompt text above is reproduced verbatim from a public
source. Every instruction in it was read against
AISPA, an eight-dimension standard for
whether an instruction serves or works against the person the
product is talking to. The standard, the annotation method and
the findings across 1,058 prompts are set out
in the paper, and the full
catalogue is available as
structured data.
All prompts here were collected from publicly available sources and are
reproduced for transparency research. Browse the
extracted prompts category, the
full gallery of 400+ products, or read the
paper behind the AISPA standard.