tools/sentry/SKILL.md
Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.
npx skillsauth add letta-ai/skills sentryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SENTRY_AUTH_TOKEN (read-only scopes such as project:read, event:read) or to log in and create one before running commands.SENTRY_AUTH_TOKEN as an env var.SENTRY_ORG, SENTRY_PROJECT, SENTRY_BASE_URL.{your-org}/{your-project}, time range 24h, environment prod, limit 20 (max 50).If the token is missing, give the user these steps:
project:read, event:read, and org:read.SENTRY_AUTH_TOKEN as an environment variable in their system.Use scripts/sentry_api.py for deterministic API calls. It handles pagination and retries once on transient errors.
# Set to the directory containing this SKILL.md
export SENTRY_API="<path-to-skill>/scripts/sentry_api.py"
Replace <path-to-skill> with the actual skill installation directory (e.g. .skills/sentry or ~/.letta/skills/sentry).
python3 "$SENTRY_API" \
list-issues \
--org {your-org} \
--project {your-project} \
--environment prod \
--time-range 24h \
--limit 20 \
--query "is:unresolved"
python3 "$SENTRY_API" \
list-issues \
--org {your-org} \
--project {your-project} \
--query "ABC-123" \
--limit 1
Use the returned id for issue detail or events.
python3 "$SENTRY_API" \
issue-detail \
1234567890
python3 "$SENTRY_API" \
issue-events \
1234567890 \
--limit 20
python3 "$SENTRY_API" \
event-detail \
--org {your-org} \
--project {your-project} \
abcdef1234567890
Always use these endpoints (GET only):
/api/0/projects/{org_slug}/{project_slug}/issues//api/0/issues/{issue_id}//api/0/issues/{issue_id}/events//api/0/projects/{org_slug}/{project_slug}/events/{event_id}/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.{your-org}{your-project}{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.
testing
Navigates archived ChatGPT or Claude-style conversation exports and a MemFS reference archive on demand. Use when recalling what a past assistant knew, searching old conversations, rendering specific chats, seeding reference memory from export sidecars, or mining historical context without doing a full import.
testing
Migrates deprecated Letta Filesystem folders/files to MemFS using markdown document corpora, chunking, local lexical search, and QMD semantic search via the memfs-search skill. Use when replacing folders.files.upload, working with PDFs or document QA, or emulating open_file, grep_file, and search_file behavior.
data-ai
Configures Letta agent compaction settings and custom summarization prompts. Use when a user asks to change an agent's compaction prompt, improve summaries after context eviction, tune sliding-window or all-message compaction, or design companion/coding-agent continuity summaries.
development
Semantic search over agent memory files. Use when you need to find conceptually related memory blocks, discover forgotten reference files, check what you already know before creating new memory, or search beyond exact keyword matching. Currently supports QMD (local, no API keys).