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ai-issue-report
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ai-issue-report — report the fault, collect nothing on the way
What it produces
A local draft (gitignored) plus the exact bytes that would leave, previewed with their SHA-256 — and nothing sent by anybody but the user.
The non-negotiable: what must never leave the machine
The payload is closed to allow-listed fields. Everything else is rejected at the gate, before the draft exists:
- Machine paths — home directories and absolute paths on any OS: they leak the
username and the project layout. The scan names the field and the match
(
ACCEPTANCE_MACHINE_PATH_*); the fix is to describe the same thing without the path. - Personal data (PII) — emails, names, phone numbers, account ids, tokens in URLs.
ACCEPTANCE_PII_*names what was found; rewrite the sentence, not around the value. - Secrets — keys, passwords, session cookies, anything gitleaks would flag.
ACCEPTANCE_GITLEAKS_SECRETis a hard refusal: no draft is written at all. - Logs, diffs, tracebacks, full command lines — there is no field for them, by design. A pasted command carries the path it ran from and often the arguments it ran with. Write the four fields in your own words instead: title, what happened, what you expected, one step per reproduction step.
A vulnerability (--kind security) NEVER becomes a public issue: the refusal prints the
private disclosure route (SECURITY.md, the maintainer's security contact) and declines the
public one before asking anything.
Steps
- Reproduce it first. A report of something that happened once is a report the person reading it cannot act on; the steps field is what makes the difference.
- Decide the kind before writing. Security → private route, always.
- Write the four fields in your own words. Never paste logs, diffs or tracebacks.
- Run the gate. Read the refusal if you get one: each code names what was found and in which field. Rewrite that field in words that do not carry the value — do not work around the scan.
- Read the previewed bytes and their SHA-256. They are exactly what would leave. If anything in there is not yours to publish, stop.
- Sending is separate and manual. Nothing is transmitted automatically: take the previewed bytes to the route your organisation or the upstream project uses (GitHub issue for bugs, SECURITY.md contact for vulnerabilities, your incident channel for incidents).
Writing the prose
The write-up follows the framework's single writing standard — read it before writing the fields: ai-write › references/documentation-writer.md. One idea per sentence, one meaning per word, nothing the environment already says. When the report is long (an incident post-mortem rather than a bug), hand the prose to /ai-write and keep this skill's gate as the last step before publishing.
The ai-engineering seam
- The governed post-mortem lives at
.ai-engineering/reports/NNN-{slug}.html— readable without session context; the NNN numbering is never rewritten. - It is immune while DECISIONS.md cites it; uncited, it expires to gc (§21.3) — history is not rewritten, it is archived in git.
- The gate (paths/PII/secrets) runs on ANY text destined to leave a governed repo — it is the same discipline the git floor's gitleaks stage enforces at commit time, applied one step earlier, to prose.
Routing
In scope: reproducible faults bound for a team, an upstream project, or an incident review. Not for: undiagnosed faults (/ai-debug), internal findings worth remembering (/ai-note), decisions (/ai-plan), the docs themselves (/ai-write).
Lifecycle
Lane: any Writes: .ai-engineering/reports/NNN-{slug}.html Read by: the team, humans without session context Dies: immune while a permanent governor cites it; doctor --gc after older_than when nothing cites it Next: none
Source: ai-engineering v1 skill ai-report (own), Apache-2.0 — renamed ai-issue-report.
File metadata
name: ai-issue-report description: >- Reports a reproducible fault to a team or an upstream project — for ai-engineering itself or for any service the client is building — as a governed payload: closed allow-listed fields, scanned for machine paths, personal data (PII) and secrets before anything is written, draft kept local, and the exact bytes shown with their SHA-256 before anybody confirms anything. Trigger for "report this bug", "file an issue", "the framework is broken", "send this upstream", "write the incident report". Not for a fault in your own code that still needs a diagnosis — use /ai-debug first. Not for a vulnerability sent anywhere public: that routes to private disclosure, and this skill refuses the other way. license: Apache-2.0
View original text
---
name: ai-issue-report
description: >-
Reports a reproducible fault to a team or an upstream project — for ai-engineering itself
or for any service the client is building — as a governed payload: closed allow-listed
fields, scanned for machine paths, personal data (PII) and secrets before anything is
written, draft kept local, and the exact bytes shown with their SHA-256 before anybody
confirms anything. Trigger for "report this bug", "file an issue", "the framework is
broken", "send this upstream", "write the incident report". Not for a fault in your own
code that still needs a diagnosis — use /ai-debug first. Not for a vulnerability sent
anywhere public: that routes to private disclosure, and this skill refuses the other way.
license: Apache-2.0
---
# ai-issue-report — report the fault, collect nothing on the way
## What it produces
A local draft (gitignored) plus the exact bytes that would leave, previewed with their
SHA-256 — and nothing sent by anybody but the user.
## The non-negotiable: what must never leave the machine
The payload is closed to allow-listed fields. Everything else is rejected at the gate,
before the draft exists:
- **Machine paths** — home directories and absolute paths on any OS: they leak the
username and the project layout. The scan names the field and the match
(`ACCEPTANCE_MACHINE_PATH_*`); the fix is to describe the same thing without the path.
- **Personal data (PII)** — emails, names, phone numbers, account ids, tokens in URLs.
`ACCEPTANCE_PII_*` names what was found; rewrite the sentence, not around the value.
- **Secrets** — keys, passwords, session cookies, anything gitleaks would flag.
`ACCEPTANCE_GITLEAKS_SECRET` is a hard refusal: no draft is written at all.
- **Logs, diffs, tracebacks, full command lines** — there is no field for them, by design.
A pasted command carries the path it ran from and often the arguments it ran with. Write
the four fields in your own words instead: title, what happened, what you expected, one
step per reproduction step.
A vulnerability (`--kind security`) NEVER becomes a public issue: the refusal prints the
private disclosure route (SECURITY.md, the maintainer's security contact) and declines the
public one before asking anything.
## Steps
1. Reproduce it first. A report of something that happened once is a report the person
reading it cannot act on; the steps field is what makes the difference.
2. Decide the kind before writing. Security → private route, always.
3. Write the four fields in your own words. Never paste logs, diffs or tracebacks.
4. Run the gate. Read the refusal if you get one: each code names what was found and in
which field. Rewrite that field in words that do not carry the value — do not work
around the scan.
5. Read the previewed bytes and their SHA-256. They are exactly what would leave. If
anything in there is not yours to publish, stop.
6. Sending is separate and manual. Nothing is transmitted automatically: take the previewed
bytes to the route your organisation or the upstream project uses (GitHub issue for
bugs, SECURITY.md contact for vulnerabilities, your incident channel for incidents).
## Writing the prose
The write-up follows the framework's single writing standard — read it before writing the
fields: [ai-write › references/documentation-writer.md](../ai-write/references/documentation-writer.md).
One idea per sentence, one meaning per word, nothing the environment already says. When the
report is long (an incident post-mortem rather than a bug), hand the prose to /ai-write and
keep this skill's gate as the last step before publishing.
## The ai-engineering seam
1. The governed post-mortem lives at `.ai-engineering/reports/NNN-{slug}.html` — readable
without session context; the NNN numbering is never rewritten.
2. It is immune while DECISIONS.md cites it; uncited, it expires to gc (§21.3) — history is
not rewritten, it is archived in git.
3. The gate (paths/PII/secrets) runs on ANY text destined to leave a governed repo — it is
the same discipline the git floor's gitleaks stage enforces at commit time, applied one
step earlier, to prose.
## Routing
In scope: reproducible faults bound for a team, an upstream project, or an incident review.
Not for: undiagnosed faults (/ai-debug), internal findings worth remembering (/ai-note),
decisions (/ai-plan), the docs themselves (/ai-write).
## Lifecycle
Lane: any
Writes: .ai-engineering/reports/NNN-{slug}.html
Read by: the team, humans without session context
Dies: immune while a permanent governor cites it; doctor --gc after older_than when nothing cites it
Next: none
Source: ai-engineering v1 skill `ai-report` (own), Apache-2.0 — renamed ai-issue-report.
Review the source
Price & running costs
- Get the skill
- Price unconfirmed
- Run it
- Requirements have not been confirmed. Check the source for agent, API and service charges.
- License
- Apache-2.0
- Price unconfirmed
- We have not confirmed a price for this skill. Existing source and install links remain available.
Free to get does not mean free to run. Price labels are not safety ratings. Submit pricing information →
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: Apache-2.0
- Permission surface may require sandboxing
- AI review approval is missing
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 55 GitHub stars
- Stars/forks activity: 55 stars, 3 forks; issue activity unavailable in current metadata
- README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context
- Permission surface: secrets or environment access, shell or command execution
- Review status: AI review approval is missing
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Start with one small task
- 1Read the source. Confirm the input, expected output, dependencies and permissions.
- 2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
- 3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.
Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.
Source & usage notes
IndexedStatic Checked
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
- Source repository
- arcasilesgroup/ai-engineering
- License
- Apache-2.0
- Version
- Unknown
- Last GitHub push
- Sep 16, 2026
- Registry updated
- Sep 16, 2026
- Instruction path
- skills/ai-issue-report/SKILL.md @ f7ea1cfd3d10
Version reported in registry metadata; check source releases before relying on it.
Quality
59/100
Promising
Trust
61/100
Sandbox only
Audit
74/100
Needs review
- Permission surface may require sandboxing
- AI review approval is missing
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 55 GitHub stars
- Stars/forks activity: 55 stars, 3 forks; issue activity unavailable in current metadata
- README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context
- Permission surface: secrets or environment access, shell or command execution
- Review status: AI review approval is missing
- Verified installs
- —
- Outcomes
- —
Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.
Agent access
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
More details
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}For the creator
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