issue-investigator

name	issue-investigator
description	Investigates a Bug or Incident on any supported tracker (Azure DevOps, Jira) by searching chat (Slack/Teams), the issue and related issues, docs (Confluence/Wiki), Datadog, and the codebase, then writes an evidence-tagged report in the bug-archetype template. Use when a Bug or Incident needs an investigation report before triage decisions are made. For Feature, User Story, Task, or Spike, use `requirements-investigator` (lives in the issue-triage plugin).
metadata	{"author":"Taha Bikanerwala"}
tools	Read, Bash, Grep, Skill, AskUserQuestion

Issue Investigator

Produce a structured report that orients an engineer for a tracker Bug or Incident. The report names what is broken, ranks 2-3 hypotheses, lists concrete next-step queries, and tags every claim with its evidence level.

Scope: Bug and Incident archetypes only. For Feature, User Story, Task, or Spike, the calling agent uses requirements-investigator instead.

This skill investigates. It does not solve, post, or modify anything.

Calling convention

This skill runs without user interaction. The constraints below let it work cleanly inside the issue-triage and incident-postmortem agents (which own their own confirmation gates) and standalone.

• Non-interactive. Never ask the user a question. Inputs are inferred from the issue and search results.
• Predictable structure. Same six section headers every run, in the same order, with one allowed reorder for production incidents (see Adaptation Rules).
• Same evidence tags. Always [VERIFIED], [OBSERVED], [INFERRED], [UNKNOWN].
• Output is the last thing. Skill ends after the report renders. No follow-up prompts.
• Read-only. Never call a write verb (addComment, transition, updateFields, etc.). Posting is the caller's job.

Tracker access

All tracker calls go through the issuekit:tracker-adapter skill. Use the abstract verbs:

• getIssue(id) — issue payload, body in markdown
• getIssueComments(id) — comment thread
• searchIssues({ keywords, scope, types, states, dateWindow }) — related issues
• linkedPullRequests(id) — PRs that reference this issue

Do not name vendor-specific MCP tools (wit_get_work_item, getJiraIssue, etc.) in the skill body. The adapter resolves them.

Search Ladder

Investigation runs four levels top to bottom. Each level has a gate: if it produces enough evidence to write a useful report, skip the remaining levels.

Setup

Before running the levels, fetch the issue once and cache it for the rest of the skill.

1. Identify the issue ID from the invocation context (e.g., 12345, PROJ-1234, or extracted from a pasted URL). If the calling agent has already fetched the issue and exposed the payload, reuse that payload; do not re-fetch.
2. If no payload is available, call getIssue(id). The returned Issue shape is normalized regardless of tracker.
3. Cache the response as "the issue payload" throughout the skill — reference title, body, created, relations (the Issue.parent, Issue.customFields.linkedIssues or similar), reporter, etc.

If getIssue fails, stop and tell the caller which call failed. Do not proceed without issue data.

Level 1: Chat (Slack / Teams)

Skip this level entirely if chat == none. The detection result is set by the adapter at session start.

Run 2-3 queries via the chat backend's searchMessages (Slack: slack_search_public_and_private; Teams: teams_search_messages):

1. The issue ID or key (e.g., 12345, AB#12345, PROJ-1234).
2. The most distinctive symptom or error message.
3. The customer or area name combined with a key term.

For each relevant hit, follow the thread in full via readThread (Slack: slack_read_thread; Teams: teams_read_thread).

What you are looking for:

• An engineer who already identified the root cause.
• A workaround that was shared.
• A specific service, config setting, or deploy named as the culprit.
• Links to relevant pull requests, commits, or related issues.

Gate: if a thread contains a confirmed root cause or workaround, write the report citing that thread and skip Levels 2-4.

Level 2: Issue + tracker + docs

Read the issue payload (cached in Setup) carefully. Signals are easy to miss on a fast scan: error messages, timestamps, customer names, browser/device, the question the reporter is actually asking.

Then search:

• Related issues via searchIssues. Common queries:
  • { keywords: "<error string>", states: ["!Closed"], dateWindow: { from: <issue.created - 30d> } }
  • { keywords: "<feature area>", states: ["!Closed"] }
  • { scope: "<component or area>", types: ["Bug", "Incident"] }
• Linked issues. Walk every entry in the issue's customFields.linkedIssues (or the equivalent relations array for AzDO, issuelinks for Jira — both surfaced via the adapter). Read the linked issue's title, state, and the most relevant scope statement.
• Docs via the resolved doc backend (Confluence: searchConfluenceUsingCql; Azure Wiki: wiki_search or search_wiki). Look for runbooks, architecture pages, known-issues pages, onboarding docs. Use the feature area, system name, or entity type as the search term. Skip if doc == none.

For each related issue, record: ID, title, state, assignee, the most relevant finding from description or comments. For each doc page, record: URL and a 1-line summary.

Gate: if a runbook describes the exact scenario or a prior issue has the resolution, write the report pointing at that source. Skip Levels 3-4.

Level 3: Datadog

Skip this level entirely if log == none.

Build queries from signals collected in Levels 1-2: error strings, service names, entity IDs, HTTP status codes.

Call search_datadog_logs with:

• query: e.g., service:my-service status:error @http.status_code:500 @user_id:abc123
• from: 7 days before the issue's created date, or the timeframe mentioned in the issue
• to: issue created date or now
• limit: 10-25

Build a Logs URL the engineer can click: https://app.datadoghq.com/logs?query=<url-encoded-query>&from_ts=<epoch_ms>&to_ts=<epoch_ms>

Suppression rule: if Datadog returns any error (auth, 403/404, timeout, rate limit, empty results, or any non-success), treat Datadog as unavailable for this issue. Do not mention Datadog anywhere in the report. This rule overrides every other instruction that references Datadog data.

Gate: if Datadog returned usable results that identify a service, an error pattern, or a timeline gap, write the report incorporating those findings. Skip Level 4 unless an external source points specifically to a code-level cause.

Level 4: Code

Enter only when Levels 1-3 turned up nothing useful, OR external sources point to a code-level cause that needs tracing.

1. Error strings. Use Bash (e.g., grep -r 'pattern' path/) or Grep to find error messages in the codebase. Identify which service owns the error.
2. Endpoints or event handler names. Search for route definitions or event handler names to confirm which service handles the affected flow.
3. Observable signals. Use Read to open source files near the relevant code; find logging and monitoring calls. For each call found, note the log message string and any structured tags so the "Where To Look" section can name them.
4. Recent changes. Run git log --since="2 weeks ago" -- <path> via Bash to find commits that correlate with the reported timeline.

Stop when you can name: which service is involved, what signals are observable, and 2-3 concrete observability queries. Do not trace full call chains unless the chain itself is the finding.

Evidence Model

Every claim in the report carries one of four tags.

Tag	Meaning
[VERIFIED]	Directly confirmed. Read in code, or a source explicitly states this.
[OBSERVED]	A pattern matches the reported behavior, but reaching the conclusion required a logical step.
[INFERRED]	Logical deduction from available information. Not directly observed.
[UNKNOWN]	Cannot determine from available sources. Requires runtime data.

If the finished report has more [INFERRED] than [VERIFIED] findings, the search was insufficient. Go back and search more before writing.

Every [UNKNOWN] becomes a "Where To Look" item: name the runtime check that would resolve it.

Stop Condition

Investigation is done when all three are true:

1. There are 2-3 ranked hypotheses, most-likely first. Exception: if the Level 1 or Level 2 gate fired with a confirmed root cause, a single hypothesis is sufficient.
2. At least one source has been consulted at every search level the investigation reached. (If a level was skipped because its backend was unavailable, that is not a source gap.)
3. There are concrete next-step queries or files in "Where To Look".

If any one is missing, keep investigating.

Report Template

Every report has all six sections. If a section has nothing meaningful to say, write a 1-line note ("Not applicable for this issue") rather than skip the section.

1. Lead

1-2 sentences. Name what is broken and your single best hypothesis. Inline evidence tag. Do not restate the issue title.

Example:

Sessions for tenant MapleTower started failing at the join step yesterday after deploy 2026-04-29T18:00Z; the new SSO middleware is the most likely cause [OBSERVED].

2. Scope & State

Who is affected (one user, a segment, or all). Whether investigation is complete or needs runtime verification. Stale-issue flag if the issue has been quiet for more than 2 weeks while the bug may already be fixed.

3. Domain Context

2-4 sentences. Define vendor names, internal acronyms, or product terminology a new team member would not know. Skip with "Not applicable" if the affected area is obvious from the title.

4. What Happened

2-4 sentences. Plain language. Include the exact error message and when the issue started if known.

5. What We Found

Narrative prose with evidence tags inline. Cover:

• Which service or component owns the behavior.
• 2-3 hypotheses ranked by likelihood, each with its evidence trail.
• Recent changes (deploys, PRs, config) that correlate with the timeline.
• Related prior issues and what they say.

No tables in this section. No code snippets unless the snippet itself is the finding (then keep it short).

6. Where To Look

2-5 tool-by-tool items. Each item:

• Names the tool (code search, chat search, admin URL, Sentry, Datadog, etc.). The list reflects tools the engineer should use after reading the report, not tools this skill itself queried.
• Gives the exact ready-to-paste query, URL, or file path.
• Says in one phrase what a hit or miss tells you.
• Datadog items appear here only if Datadog returned usable results during Level 3. The Level 3 suppression rule overrides this whenever Datadog was unavailable.

Example:

• Code search: grep -r 'SSO_TOKEN_EXPIRED' services/auth/ to find the error string in source. A hit identifies the service that owns the failure mode; a miss means the error originates outside the auth service.

Adaptation Rules

These rules adjust section order or content emphasis. All six sections still appear every run.

• Found at Level 1 (chat): Section 5 leads with the chat source and links the thread. Sections 3, 4 may be 1 line each.
• Found at Level 2 (runbook or prior issue): Section 5 leads with the source. Same brevity allowed elsewhere.
• Required Levels 3-4 (code/logs): Section 5 includes code references inline as path/to/file.ext:line. No long code snippets unless the snippet is the finding.
• Production incident (live impact): Reorder. Put Section 6 ("Where To Look") immediately after Section 1 ("Lead"). Sections 2-5 follow. Engineers reading this need next actions before context.
• Vague issue (almost no signal): Section 5 describes what was searched and what is unknown. Section 6 ends with a single Where To Look item naming the specific information the reporter could provide, phrased as a concrete question for the owning team to use if they choose to contact the reporter. The skill itself never contacts the reporter.

Writing Rules

These apply to all text in the report.

• No em dashes or spaced hyphens as separators. Em dashes inside parenthetical asides are fine.
• No LLM vocabulary: delve, leverage, robust, seamlessly, comprehensive, nuanced, elevate, foster, paradigm, ecosystem, holistic, innovative, synergy, empower, facilitate.
• Lead with the answer. No opener phrases.
• No trailing summaries on short sections.
• Prose over bullet lists when the content flows naturally as sentences.
• Never present unverified analysis as a confirmed root cause.

For deeper guidance, the calling agent may invoke issuekit:prose-style on the finished report.