Fix Sentry Issues
brianlovin/agent-config
Use Sentry MCP to discover, triage, and fix production issues with root-cause analysis.
Root-cause a specific Opik trace, or a pattern across traces, and return a grounded explanation.
$ npx skills add comet-ml/opik-mcp --skill opik-explain -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install comet-ml/opik-mcp opik-explain --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/comet-ml/opik-mcp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/opik_mcp/skills/opik-explain .claude/skills/opik-explain && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "opik-explain" agent skill from https://github.com/comet-ml/opik-mcp/tree/main/src/opik_mcp/skills/opik-explain into .claude/skills/opik-explain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "opik-explain", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/comet-ml/opik-mcp/tree/main/src/opik_mcp/skills/opik-explainType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add comet-ml/opik-mcp --skill opik-explain -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install comet-ml/opik-mcp opik-explain --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/comet-ml/opik-mcp.git skills-src && mkdir -p .agents/skills && cp -r skills-src/src/opik_mcp/skills/opik-explain .agents/skills/opik-explain && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "opik-explain" agent skill from https://github.com/comet-ml/opik-mcp/tree/main/src/opik_mcp/skills/opik-explain into .agents/skills/opik-explain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "opik-explain", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add comet-ml/opik-mcp --skill opik-explain -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install comet-ml/opik-mcp opik-explain --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/comet-ml/opik-mcp.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/src/opik_mcp/skills/opik-explain .cursor/skills/opik-explain && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "opik-explain" agent skill from https://github.com/comet-ml/opik-mcp/tree/main/src/opik_mcp/skills/opik-explain into .cursor/skills/opik-explain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "opik-explain", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/comet-ml/opik-mcp.git --path src/opik_mcp/skills/opik-explain--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add comet-ml/opik-mcp --skill opik-explain -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install comet-ml/opik-mcp opik-explain --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/comet-ml/opik-mcp.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/src/opik_mcp/skills/opik-explain .gemini/skills/opik-explain && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "opik-explain" agent skill from https://github.com/comet-ml/opik-mcp/tree/main/src/opik_mcp/skills/opik-explain into .gemini/skills/opik-explain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "opik-explain", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install comet-ml/opik-mcp opik-explainInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add comet-ml/opik-mcp --skill opik-explain -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/comet-ml/opik-mcp.git skills-src && mkdir -p .github/skills && cp -r skills-src/src/opik_mcp/skills/opik-explain .github/skills/opik-explain && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "opik-explain" agent skill from https://github.com/comet-ml/opik-mcp/tree/main/src/opik_mcp/skills/opik-explain into .github/skills/opik-explain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "opik-explain", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add comet-ml/opik-mcp --skill opik-explain -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install comet-ml/opik-mcp opik-explain --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/comet-ml/opik-mcp.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/src/opik_mcp/skills/opik-explain .opencode/skills/opik-explain && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "opik-explain" agent skill from https://github.com/comet-ml/opik-mcp/tree/main/src/opik_mcp/skills/opik-explain into .opencode/skills/opik-explain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "opik-explain", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
opik-explainRoot-cause a specific Opik trace, or a pattern across traces, and return a grounded explanation.
Opik Explain is an agent skill from comet-ml/opik-mcp. Root-cause a specific Opik trace, or a pattern across traces, and return a grounded explanation. Uses the hosted Opik MCP when it is connected, and falls back to SDK scripting otherwise. Returns the root cause, the evidence spans as clickable Opik UI links, and one suggested next step. Use for "why did this trace fail", "explain this trace", "debug this trace", "why is my agent slow or wrong". Not for adding tracing to an app (use the instrument skill) or for changing code.
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files (for example `evals/HARNESS.md`, `evals/cases.yaml` and `evals/fixtures/latency/agent.py`). Compatibility notes: Tested with Claude Code; works with any Agent Skills-compatible host (Cursor, VS Code Copilot, Codex). Requires a Python or TypeScript project with Opik…
It sits in Agent Workflows, covering Root cause analysis and MCP servers. It works with Model Context Protocol. The repository describes itself as: Model Context Protocol (MCP) server for Opik, the open-source LLM observability and evaluation platform, built by Comet. Read traces, log scores, and manage prompts from Claude… The licence is Apache-2.0.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e0c2057. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadGrepGlobBashFrom allowed-tools in the SKILL.md frontmatter.
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
comet.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
OPIK_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Tested with Claude Code; works with any Agent Skills-compatible host (Cursor, VS Code Copilot, Codex). Requires a Python or TypeScript project with Opik configured and at least one trace. Install the `opik` skill alongside this one — it holds the shared SDK and observability references; without it, this skill falls back to the public docs.
From compatibility in the SKILL.md frontmatter.
Opik Explain loads about 2.4k tokens when it runs. Until then it costs about 123 tokens; SKILL.md has 1,012 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: Read, Grep, Glob, BashAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from comet-ml/opik-mcp at commit e0c2057, republished under its Apache-2.0 licence (© comet-ml). 1,012 words, ~2,413 tokens.
.claude/skills/opik-explain/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.Definition of done: a grounded root cause for the requested trace (or pattern), tied to specific evidence spans and paired with exactly one suggested next step. "Grounded" means the explanation names the failing/anomalous span and connects it to the code or data that produced it — not a restatement of the trace. If the target can't be fetched or read, stop at the first genuine blocker and return one concrete next step. A trace dump is not an explanation.
Operate: investigate over the real trace data, reason against the repo, commit to a single most-likely root cause with its evidence — and change no code. This skill is read-only by design.
The entry point is /opik-explain <trace-id> (one trace) or /opik-explain <describe the behavior> (a pattern to find and explain). Infer the rest; treat these as optional overrides:
Ask only at a genuine, non-inferable blocker (see Blockers).
~/.opik.config exists or OPIK_API_KEY is set, use it. Otherwise → Blocker ("run opik configure, then rerun").Check whether the hosted Opik MCP is connected and prefer it; fall back to SDK scripting when it isn't.
read the trace and list/read its spans.Either way, read every span's input/output/error/duration.
import opik
client = opik.Opik()
tid = "<trace_id>"
trace = client.get_trace_content(
tid
) # TracePublic: exposes project_id, input, output, error info — NOT project_name (accessing .project_name raises)
project = client.rest_client.projects.get_project_by_id(trace.project_id).name
spans = client.search_spans(
project_name=project, trace_id=tid
) # spans come from a SEPARATE call, not from the trace object
# ALWAYS pass project_name: without it the SDK searches the configured default project, which
# returns an empty list (or a 404 if that project doesn't exist) even for a valid trace id.
# Reconstruct the tree via each span's parent_span_id (the root span has none).
# Your anchor is the first span that errored, returned wrong output, or dominates the duration.For a pattern, pull the matching set scoped to the project, then look for the shared failing span across them. With the MCP, one list call does the filtering and ordering server-side — filters is an OQL string, sort is "<field> [asc|desc]", since takes "1h" / "7d":
list(entity_type="trace", project_name="<project>", since="7d",
filters="error_info is_not_empty", sort="start_time desc") # error traces
list(entity_type="trace", project_name="<project>", since="7d",
sort="duration desc") # slow traces (duration in ms)
list(entity_type="trace", project_name="<project>", since="7d",
filters="feedback_scores.hallucination > 0.5") # low-scored traces
list(entity_type="span", project_name="<project>", since="7d",
filters='name = "<span name>" AND error_info is_not_empty') # the shared failing span, across tracesThe applied filter is echoed on the first line; a rejected one comes back with what fixes it (schema("list.trace") is the full field reference). Without the MCP, the SDK takes the same grammar:
traces = client.search_traces(project_name="<project>", filter_string="error_info is_not_empty")Traces are asynchronous; if you just produced the trace, allow a few seconds and confirm the flush ran.
The coding agent root-causes over the fetched data, against the repo — it has the one thing a generic reasoner lacks: the code. Whether the trace came from the MCP or the SDK, the analysis is the same: find the anchor span (error / wrong output / latency dominator), read its input and output, connect it to the code (grep the repo for the span name / function), and state the single most-likely root cause with its evidence spans. Prefer one well-evidenced cause over a list of maybes.
Return the root cause, the evidence spans as clickable Opik UI links (the trace redirect URL Opik emits, e.g. .../session/redirect/...?trace_id=THE_ID — never a bare id), and one next step (see Output). If a fix is obvious, name it as the next step; do not apply it (this skill changes no code — handing off to opik-instrument/opik-test or the developer is the next step).
Stop at the earliest blocker and return exactly one next step:
opik configure, then rerun /opik-explain <trace-id>."<id> in project <name> — confirm the id and project, then rerun."User-facing: a short human message — the root cause in one or two sentences, the evidence spans as clickable Opik UI links (name + why each matters), and the single next step. Not a raw trace dump, not JSON.
Underneath (for composition / evals), one shape whether the MCP or the SDK path produced it:
status: explained | blocked | not_foundtarget: trace_id + trace_url (the Opik UI link; for a pattern, the trace_ids + trace_urls sampled)root_cause: one grounded statementevidence: spans (each: name, type, a trace_url deep-link where available, why it's evidence)next_step: exactly onereasoner: agent (the coding agent root-causes over the trace data and the repo)Invariants: explained must carry a root_cause and at least one evidence span; blocked/not_found carry exactly one next_step; every path leaves the codebase unchanged.
Single trace — tool failure. /opik-explain 019fd8a7-.... Fetch trace + spans; the retrieve (tool) span returned empty and the llm span then hallucinated. Open retrieve() in the repo: the query filter is wrong. Root cause = the retrieval filter, evidence = the empty tool span feeding the llm span; next step = "fix the filter in retrieve() (or /opik-test it)". → explained.
Pattern — slowness. /opik-explain why responses got slow this week. list('trace', since="7d", sort="duration desc") (or search_traces without the MCP) for the slowest traces; the same external tool span dominates each. Root cause = that call's latency; evidence = the shared slow span across N traces; next step = "add a timeout/cache around it". → explained.
Blocked — bad id. /opik-explain 123. get_trace_content finds nothing. → not_found: "No trace 123 in project X — confirm the id/project and rerun." (No code touched.)
Dumping the span tree without naming a cause; guessing a cause without reading the anchor span's input/output; listing five maybes instead of the one best-evidenced cause; returning bare span/trace ids instead of clickable Opik UI links; editing code (this skill explains; opik-instrument/opik-test or the developer make changes); calling .project_name on a TracePublic (it raises — use project_id); calling search_spans(trace_id=…) without project_name (it searches the default project and comes back empty).
SDK and observability detail live in the opik skill, installed beside this one. Read the files directly — paths are relative to this file: ../opik/SKILL.md (Searching traces — the OQL filter grammar shared by the MCP list tool and search_traces), ../opik/references/production.md (search_traces, error/latency/cost analysis), ../opik/references/tracing-python.md (SDK read APIs), ../opik/references/observability.md (span-type model). If your host lays skills out differently, locate the opik skill's references/ directory.
If the opik skill isn't installed, say so in the report and use https://www.comet.com/docs/opik/ rather than working from memory.
© comet-ml, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 10 other files in src/opik_mcp/skills/opik-explain of comet-ml/opik-mcp.
Open the folder on GitHubat commit e0c2057
Opik Explain next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Opik Explain this skillcomet-ml/opik-mcp | 219 | — | ~2.4k | Automated safety check: Notes | Apache-2.0 | |
| Fix Sentry Issuesbrianlovin/agent-config | 376 | 1 repos | ~1.2k | Automated safety check: Pass | None | |
| Flowstudio Power Automate Debuggithub/awesome-copilot | 40k | 2 repos | ~5k | Automated safety check: Pass | MIT | |
| QA Find Bugs MCPbex-co/beancount-io | 295 | — | ~3k | Automated safety check: Pass | MIT | |
| Monte Carlo Remediationsickn33/agentic-awesome-skills | 47k | 1 repos | ~4k | Automated safety check: Pass | Apache-2.0 | |
| Debugagentic-community/mcp-gateway-registry | 964 | — | ~1.8k | Automated safety check: Notes | Apache-2.0 |
brianlovin/agent-config
Use Sentry MCP to discover, triage, and fix production issues with root-cause analysis.
github/awesome-copilot
Debug failing Power Automate cloud flows using the FlowStudio MCP server.
bex-co/beancount-io
Hunt bugs in the Beancount.io remote MCP server by driving the real POST /api-gateway/mcp endpoint with JSON-RPC and real MCP clients, checking transport, discovery, credential boundaries, tool and…
sickn33/agentic-awesome-skills
Investigate and remediate data quality alerts using Monte Carlo MCP tools.
agentic-community/mcp-gateway-registry
Debug issues in the MCP Gateway Registry using first-principles thinking.
github/awesome-copilot
Pro+ subscription required. An agent skill from github/awesome-copilot.
comet-ml/opik-mcp
Reference for the Opik SDK — tracing, span types, framework integrations, threads, and the prompt library (Python, TypeScript, REST).
comet-ml/opik-mcp
Run a candidate against the baseline over an Opik test suite and read the numbers back — which cases broke, which got fixed, the per-metric deltas, worst rows, and whether the two runs are…
comet-ml/opik-mcp
Surface the Opik traces worth a developer's attention, ranked by signal — Diagnostics issues first, then errors, failed tool calls, latency, regressions, and low online-eval scores.
comet-ml/opik-mcp
Build an LLM evaluation and run it against the app, returning an Opik experiment with scores and its link.
comet-ml/opik-mcp
Add Opik tracing to an existing app and verify a real trace lands.
comet-ml/opik-mcp
Improve a prompt with the Opik Agent Optimizer — resolve the prompt, a dataset, and a metric, pick the algorithm, run a bounded optimization, check the gain on held-out data, and save the winner as…
Works with
Categories
Root-cause a specific Opik trace, or a pattern across traces, and return a grounded explanation. Opik Explain is an agent skill from comet-ml/opik-mcp. Root-cause a specific Opik trace, or a pattern across traces, and return a grounded explanation.
Opik Explain fits situations like: why did this trace fail; explain this trace; debug this trace; why is my agent slow.
Run `npx skills add comet-ml/opik-mcp --skill opik-explain -a claude-code`. Or copy the skill folder (src/opik_mcp/skills/opik-explain in comet-ml/opik-mcp) into .claude/skills/opik-explain in your project. Claude Code loads it when a task matches its description.
Run `npx skills add comet-ml/opik-mcp --skill opik-explain -a codex`. Or copy the skill folder (src/opik_mcp/skills/opik-explain in comet-ml/opik-mcp) into .agents/skills/opik-explain in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add comet-ml/opik-mcp --skill opik-explain -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/opik-explain, .gemini/skills/opik-explain, .github/skills/opik-explain and .opencode/skills/opik-explain in your project.
Going by SKILL.md and its folder, Opik Explain needs Python for the scripts in its folder and credentials named OPIK_API_KEY. Our summary lists: Python 3; A credential in OPIK_API_KEY. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash. Compatibility (from SKILL.md): Tested with Claude Code; works with any Agent Skills-compatible host (Cursor, VS Code Copilot, Codex). Requires a Python or TypeScript project with Opik configured and at least one trace. Install the `opik` skill alongside this one — it holds the shared SDK and observability references; without it, this skill falls back to the public docs..
SKILL.md names 1 domain. As links in the text: comet.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Opik Explain is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.4k tokens (SKILL.md is roughly 9.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Opik Explain: Fix Sentry Issues (brianlovin/agent-config, 376 stars), Flowstudio Power Automate Debug (github/awesome-copilot, 40k stars), QA Find Bugs MCP (bex-co/beancount-io, 295 stars) and Monte Carlo Remediation (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
comet-ml (a GitHub organization) maintains it in comet-ml/opik-mcp, which has 219 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 7, 2026.
Source: comet-ml/opik-mcp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.