npx skills add ...
npx skills add cursor/plugins --skill why
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
npx skills add cursor/plugins --skill why
Investigate the motivation and intent behind code.
Companion to the how skill. how answers what the code does and how it works. why answers what forces led to its shape.
Operate as a careful, cautious, and precise investigator. Be honest about what you know vs what you're inferring. Read references/epistemics.md for the full confidence framework and phrasing guide. The synthesizer must follow it.
Parse what the user is asking. 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.
If the target is vague ("why do we do it this way?" with no clear referent), make your best guess from conversation context (open files, recent edits, cursor location, what was just discussed). State your interpretation briefly so the user can redirect if you're off, then proceed.
Before spawning investigators, anchor the investigation in concrete code. You need:
(#1234) in the subject line)Build this inline.
Pull PR bodies and discussion via gh for any substantive commits:
Capture this as seed context (file paths, symbols, commits, PR numbers, linked ticket IDs). Pass it to the investigators.
Default to the full parallel investigation.
Before spawning investigators, list the available MCPs from the Cursor environment. Use the available-tools map when present. Otherwise inspect the mcps/ directory Cursor exposes for enabled MCP servers.
Map each available MCP to one evidence category:
Source control is always available through git and gh. For the other six, classify using the MCP name, server instructions, tool names, and resource descriptors. If an MCP could fit more than one category, choose the one matching its primary evidence. Record ambiguous cases in the coverage map.
Aim for a complete coverage map, not a minimal one. Document the null, don't skip the search.
Launch all matching investigators in a single message so they run concurrently. Don't ask one agent to cover multiple MCPs.
Subagent config (each):
subagent_type: generalPurposemodel: your configured why-investigators model (default grok-4.6-fast-xhigh)readonly: false (agent mode). Do not use readonly/Ask mode. It strips MCP access, which disables MCP-backed investigators entirely. Investigators still shouldn't write anything.Each investigator gets:
references/investigator-prompt.mdreferences/sources/<source>.md for the selected MCP, adapted from the examples in references/source-playbook.mdreferences/sources/incident-postmortem.md if the target code looks defensive (null checks, retry logic, timeout handling, rate limiting, feature flags, egress guards, OOM handlers)Spawn one investigator per category that has a matching MCP. Each owns exactly one tool or MCP.
Each entry names the category and the kind of "why" it uniquely surfaces. Use it to know what to expect back, how to name a gap when a category returns empty, and (only in the rare provably-irrelevant case) to justify a skip.
Source control investigator. Git history, gh for PRs, code comments, tests. Always spawn. The only guaranteed source. Best at surfacing implementation-time rationale captured during review.
Issue / ticket tracker investigator (e.g. Linear, Jira, GitHub Issues, Plane, Shortcut MCP). Best at surfacing the product or business forcing function. Strongest when the why is external to engineering.
Long-form documents investigator (e.g. Notion, Confluence, Google Docs, Coda MCP). Best at surfacing long-form design rationale. Where the why is written out before it becomes code.
Real-time team chat investigator (e.g. Slack, Discord, Microsoft Teams, Mattermost MCP). Best at surfacing real-time deliberation that never reached a doc. Especially important when the source control, ticket, and doc paper trail is thin.
Infrastructure observability investigator (e.g. Datadog, New Relic, Honeycomb, Grafana, Splunk MCP). Infra/runtime view. Best at surfacing infrastructure and runtime reality that motivated the code. Strongest when the target reacts to an infra signal (timeouts, retries, rate limits, circuit breakers).
Error / exception tracking investigator (e.g. Sentry, Rollbar, Bugsnag, Airbrake MCP). Best at surfacing the specific exceptions and error trajectories that motivated defensive or corrective code. Strongest for catch blocks, null guards, type checks, retries, and other defenses.
Product analytics warehouse investigator (e.g. Databricks, Snowflake, BigQuery, ClickHouse, dbt, Redshift MCP). Product/data view. Best at surfacing 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 skip with an explicit, written justification that goes in the final "Sources Consulted" section. Two valid reasons:
If your scope assessment suggests a single-commit trivial target where the PR description already contains the complete answer, you may answer inline only after confirming all seven available category searches would be redundant. Say so explicitly. This should be rare.
Spawn one synthesizer subagent:
subagent_type: generalPurposemodel: your configured why-synthesizer model (default claude-fable-5-1-thinking-max)readonly: false (agent mode). The synthesizer's quality check spot-verifies citations, which can require MCP access. Readonly/Ask mode strips MCPs and defeats that.The synthesizer gets:
references/epistemics.mdreferences/synthesizer-prompt.mdTake the synthesizer's output and present it to the user. You may lightly edit for clarity or add context from the conversation, but do not rewrite the confidence language.
The output structure is the one in 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 the Sources Consulted block, if the user's why question is a precursor to actually changing this code, convert the lineage findings into a Preserve / Change / Avoid / Risk constraint set suitable for planning the change.
references/epistemics.md. Confidence tiers and phrasing guide. The synthesizer must follow it.references/investigator-prompt.md. Base prompt template for investigator subagents.references/source-playbook.md. Index pointing at the category playbooks below.references/sources/*.md. One self-contained example playbook per category, plus cross-cutting incident-postmortem.md. Give an investigator the single file that matches its category and adapt it to the available MCP.references/synthesizer-prompt.md. Prompt template for the synthesizer subagent, including the output format.*gh pr view <number> --json title,body,author,createdAt,mergedAt,labels,closingIssuesReferences,comments,reviews