git:20260923.11fd787 to git:20261014.8882c71

+ Investigate the motivation and intent behind code. The companion **how** skill (`${CLAUDE_SKILL_DIR}/../how/SKILL.md`) answers what the code does and how it works. `why` answers what forces led to its shape.

+ Every spawn uses the Agent tool with `subagent_type: "pstack:read-only"`, which keeps MCP access for the investigators and the synthesizer's citation spot-checks and blocks file edits. Models come from `${CLAUDE_SKILL_DIR}/../poteto-mode/references/models.md`.

+ The **target** is usually a chunk of code, a pattern, a feature, or a named design decision. The **question** is usually a design rationale, a tradeoff, a motivating edge case, an external constraint, dead code, or a broad history sweep.

+ Before spawning investigators, build the seed context inline: file paths and line ranges, key symbols (functions, classes, constants), the last few commits touching the target, PR numbers from merge commits (pattern `(#1234)` in the subject line), and any linked ticket IDs. Run `git blame -L <start>,<end> <file>` for last-touch commits, `git log --follow -p -- <file>` for full history with patches through renames, `git log --oneline -20 -- <file>` for recent commits with PR numbers visible, and `git log -1 --format=%B <commit>` to extract PR numbers. Then pull the PR bodies and discussion for any substantive commit: `gh pr view <number> --json title,body,author,createdAt,mergedAt,labels,closingIssuesReferences,comments,reviews`. This anchor goes to every investigator and to the synthesizer.

+ ## Step 3. Spawn Parallel Investigators

+ **Default to the full parallel investigation.** The goal is a complete coverage map, not a minimal one. Document the null, don't skip the search.

+ Spawn one investigator per category that has a matching MCP, all in a single message so they run concurrently, each owning exactly one tool or MCP. Don't ask one agent to cover multiple MCPs. `model`: the `why investigators` model.

+ Each investigator's prompt is `${CLAUDE_SKILL_DIR}/references/investigator-prompt.md` filled in, plus:

+ - the category playbook `${CLAUDE_SKILL_DIR}/references/sources/<source>.md` for the selected MCP, adapted from the examples in `${CLAUDE_SKILL_DIR}/references/source-playbook.md`

+ - `${CLAUDE_SKILL_DIR}/references/sources/incident-postmortem.md` **if the target code looks defensive** (null checks, retry logic, timeout handling, rate limiting, feature flags, egress guards, OOM handlers)

+ - the code anchor and the user's original question

+ ### Investigator roster, one per available evidence category

+ Each category below is uniquely positioned to surface one shape of "why", shown after "Best at". Use it to know what to expect back, to name a gap when a category returns empty, and, only in the rare provably-irrelevant case, to justify a skip.

+ 1. **Source control** (git history, `gh` for PRs, code comments, tests). Always spawn, the only guaranteed source. Best at *implementation-time rationale captured during review*.

+ 2. **Issue / ticket tracker** (e.g. Linear, Jira, GitHub Issues, Plane, Shortcut MCP). Best at *the product or business forcing function*. Strongest when the why is external to engineering.

+ 3. **Long-form documents** (e.g. Notion, Confluence, Google Docs, Coda MCP). Best at *long-form design rationale*, written out before it becomes code.

+ 4. **Real-time team chat** (e.g. Slack, Discord, Microsoft Teams, Mattermost MCP). Best at *real-time deliberation that never reached a doc*. Especially important when the source control, ticket, and doc paper trail is thin.

+ 5. **Infrastructure observability** (e.g. Datadog, New Relic, Honeycomb, Grafana, Splunk MCP). Best at *infrastructure and runtime reality that motivated the code*. Strongest when the target reacts to an infra signal (timeouts, retries, rate limits, circuit breakers).

+ 6. **Error / exception tracking** (e.g. Sentry, Rollbar, Bugsnag, Airbrake MCP). Best at *the specific exceptions and error trajectories that motivated defensive or corrective code*. Strongest for catch blocks, null guards, type checks, retries, and other defenses.

+ 7. **Product analytics warehouse** (e.g. Databricks, Snowflake, BigQuery, ClickHouse, dbt, Redshift MCP). Best at *product and data reality that shaped the code*. Strongest for flag-gated code, experiment-driven ships, data migrations, and "where did this number come from" questions.

+ Only with an **explicit, written justification** that goes in the final Sources Consulted. Two valid reasons:

+ - **No MCP is available for that category** in this environment. Flag it as a gap, not a choice: "Real-time team chat skipped. No matching MCP available, so the conversational record was not searchable."

+ - **The source is provably irrelevant**, not just "probably irrelevant." A high bar: "Error / exception tracking skipped. Target is a build-time script with no runtime code path."

+ Spawn one synthesizer. `model`: the `why synthesizer` model. It gets:

+ 2. The code anchor

+ Present the synthesizer's output to the user. You may lightly edit for clarity or add context from the conversation, but **do not rewrite the confidence language**.

+ The structure is the one in `${CLAUDE_SKILL_DIR}/references/synthesizer-prompt.md`: The Question, The Code in Question, What We Found, What We Can Reasonably Infer, Competing Hypotheses, What We Don't Know, Sources Consulted, Confidence Summary. Adapt as needed, but keep the confidence separation intact, and keep Sources Consulted as one line per investigator, including the ones that returned nothing or were skipped, with the reason.

+ After Sources Consulted, if the user's `why` question is a precursor to changing this code, convert the lineage findings into a Preserve / Change / Avoid / Risk constraint set for planning the change.