Awesome-omni-skills sentry

Sentry (Read-only Observability) workflow skill. Use this skill when the user needs Inspect Sentry issues, summarize production errors, and pull health data via the Sentry API (read-only). Use when user says \"check Sentry\", \"what errors in production?\", \"summarize Sentry issues\", \"recent crashes\", or \"production error report\". Requires SENTRYAUTHTOKEN. Do NOT use for setting up Sentry SDK, configuring alerts, or non-Sentry error monitoring and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

install

source · Clone the upstream repo

git clone https://github.com/diegosouzapw/awesome-omni-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills_omni/sentry" ~/.claude/skills/diegosouzapw-awesome-omni-skills-sentry-3bc67c && rm -rf "$T"

manifest: skills_omni/sentry/SKILL.md

source content

Sentry (Read-only Observability)

Overview

This public intake copy packages

packages/skills-catalog/skills/(monitoring)/sentry

from

https://github.com/tech-leads-club/agent-skills

into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

plus

ORIGIN.md

as the provenance anchor for review.

Sentry (Read-only Observability)

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Core tasks (use bundled script), Skill path (set once), API requirements, Inputs and defaults, Golden test inputs.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

Use when the request clearly matches the imported source intent: Inspect Sentry issues, summarize production errors, and pull health data via the Sentry API (read-only). Use when user says "check Sentry", "what errors in production?", "summarize Sentry issues", "recent crashes", or....
Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
Use when provenance needs to stay visible in the answer, PR, or review packet.
Use when copied upstream references, examples, or scripts materially improve the answer.
Use when the workflow should remain reviewable in the public intake repo before the private enhancer takes over.

Operating Table

Situation	Start here	Why it matters
First-time use	`metadata.json`	Confirms repository, branch, commit, and imported path before touching the copied workflow
Provenance review	`ORIGIN.md`	Gives reviewers a plain-language audit trail for the imported source
Workflow execution	`scripts/sentry_api.py`	Starts with the smallest copied file that materially changes execution
Supporting context	`LICENSE.txt`	Adds the next most relevant copied source file without loading the entire package
Handoff decision	`## Related Skills`	Helps the operator switch to a stronger native skill when the task drifts

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
Read the overview and provenance files before loading any copied upstream support files.
Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
Validate the result against the upstream expectations and the evidence you can point to in the copied files.
Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: Core tasks (use bundled script)

Use

scripts/sentry_api.py

for deterministic API calls. It handles pagination and retries once on transient errors.

Examples

Example 1: Ask for the upstream workflow directly

Use @sentry to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @sentry against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @sentry for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @sentry using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Quick start

If not already authenticated, ask the user to provide a valid
```
SENTRY_AUTH_TOKEN
```
(read-only scopes such as
```
project:read
```
,
```
event:read
```
) or to log in and create one before running commands.
Set
```
SENTRY_AUTH_TOKEN
```
as an env var.
Optional defaults:
```
SENTRY_ORG
```
,
```
SENTRY_PROJECT
```
,
```
SENTRY_BASE_URL
```
.
Defaults: org/project
```
{your-org}
```
/
```
{your-project}
```
, time range
```
24h
```
, environment
```
prod
```
, limit 20 (max 50).
Always call the Sentry API (no heuristics, no caching).

If the token is missing, give the user these steps:

Create a Sentry auth token: https://sentry.io/settings/account/api/auth-tokens/
Create a token with read-only scopes such as
```
project:read
```
,
```
event:read
```
, and
```
org:read
```
.
Set
```
SENTRY_AUTH_TOKEN
```
as an environment variable in their system.
Offer to guide them through setting the environment variable for their OS/shell if needed.

Never ask the user to paste the full token in chat. Ask them to set it locally and confirm when ready.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

Issue list: show title, shortid, status, firstseen, lastseen, count, environments, toptags; order by most recent.
Event detail: include culprit, timestamp, environment, release, url.
If no results, state explicitly.
Redact PII in output (emails, IPs). Do not print raw stack traces.
Never echo auth tokens.
Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.

Imported Operating Notes

Imported: Output formatting rules

Issue list: show title, short_id, status, first_seen, last_seen, count, environments, top_tags; order by most recent.
Event detail: include culprit, timestamp, environment, release, url.
If no results, state explicitly.
Redact PII in output (emails, IPs). Do not print raw stack traces.
Never echo auth tokens.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

packages/skills-catalog/skills/(monitoring)/sentry

, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open

metadata.json

ORIGIN.md

, and the most relevant copied upstream files. Load only the files that materially change the answer, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

```
@accessibility
```
- Use when the work is better handled by that native specialization after this imported skill establishes context.
```
@ai-cold-outreach
```
- Use when the work is better handled by that native specialization after this imported skill establishes context.
```
@ai-pricing
```
- Use when the work is better handled by that native specialization after this imported skill establishes context.
```
@ai-sdr
```
- Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Resource family	What it gives the reviewer	Example path
`references`	copied reference notes, guides, or background material from upstream	`references/n/a`
`examples`	worked examples or reusable prompts copied from upstream	`examples/n/a`
`scripts`	upstream helper scripts that change execution or validation	`scripts/sentry_api.py`
`agents`	routing or delegation notes that are genuinely part of the imported package	`agents/n/a`
`assets`	supporting assets or schemas copied from the source package	`assets/n/a`

Imported Reference Notes

Imported: Skill path (set once)

export AGENT_SKILLS_HOME="${AGENT_SKILLS_HOME:-$HOME/.agent-skills}"
export SENTRY_API="$AGENT_SKILLS_HOME/skills/sentry/scripts/sentry_api.py"

User-scoped skills install under

$AGENT_SKILLS_HOME/skills

(default:

~/.agent-skills/skills

1) List issues (ordered by most recent)

python3 "$SENTRY_API" \
  list-issues \
  --org {your-org} \
  --project {your-project} \
  --environment prod \
  --time-range 24h \
  --limit 20 \
  --query "is:unresolved"

2) Resolve an issue short ID to issue ID

python3 "$SENTRY_API" \
  list-issues \
  --org {your-org} \
  --project {your-project} \
  --query "ABC-123" \
  --limit 1

Use the returned

id

for issue detail or events.

3) Issue detail

python3 "$SENTRY_API" \
  issue-detail \
  1234567890

4) Issue events

python3 "$SENTRY_API" \
  issue-events \
  1234567890 \
  --limit 20

5) Event detail (no stack traces by default)

python3 "$SENTRY_API" \
  event-detail \
  --org {your-org} \
  --project {your-project} \
  abcdef1234567890

Imported: API requirements

Always use these endpoints (GET only):

List issues:

/api/0/projects/{org_slug}/{project_slug}/issues/

Issue detail:
```
/api/0/issues/{issue_id}/
```
Events for issue:
```
/api/0/issues/{issue_id}/events/
```

Event detail:

/api/0/projects/{org_slug}/{project_slug}/events/{event_id}/

Imported: Inputs and defaults

org_slug

project_slug

: default to

{your-org}

{your-project}

(avoid non-prod orgs).

```
time_range
```
: default
```
24h
```
(pass as
```
statsPeriod
```
).
```
environment
```
: default
```
prod
```
.
```
limit
```
: default 20, max 50 (paginate until limit reached).
```
search_query
```
: optional
```
query
```
parameter.
```
issue_short_id
```
: resolve via list-issues query first.

Imported: Golden test inputs

Org:
```
{your-org}
```
Project:
```
{your-project}
```
Issue short ID:
```
{ABC-123}
```

Example prompt: “List the top 10 open issues for prod in the last 24h.” Expected: ordered list with titles, short IDs, counts, last seen.