Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
日本語の概要は準備中です。原文の説明を表示しています。
Forensic case investigation with evidence-graded findings, calibrated to the input. Use when the user asks to investigate a bug, trace what caused an incident, walk through unfamiliar code, or build a mental model of a code area before working on it.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Reconstruct what's happening, or what an unfamiliar area does, from the available evidence. Produce a structured case file another engineer can pick up cold. Calibrate continuously between defect-chasing (symptom-driven) and area-exploration (no symptom); the same discipline applies on both ends.
Args: A ticket ID, log file path, diagnostic archive, error message, code area name, problem description, or a path to an existing case file. The last form resumes a prior investigation; everything else opens a new case.
Output: {implementation_artifacts}/{workflow.case_file_subdir}/{workflow.case_file_filename}. Reference inputs
are recorded; raw content is not read into the parent context until an outcome calls for it.
{slug} is the ticket ID when one is provided, otherwise a short descriptive name agreed with the user, sanitized to
lowercase alphanumeric with hyphens. On collision with an existing case file at the resolved path, ask whether to
rename to slug-YYYY-MM-DD.md or resume the existing file (resuming routes to Outcome 0).
After every outcome, present what was learned and pause for the user before continuing.
path:line, log timestamp, or commit hash./, so they're clickable in IDE-embedded terminals.path:line from the result; don't re-read in the parent.Resolve the workflow block by reading these three files in base → team → user order and applying the structural merge rules below:
{skill-root}/customize.toml — defaults{project-root}/.stellar-build/custom/investigate.toml — team overrides{project-root}/.stellar-build/custom/investigate.user.toml — personal overridesAny missing file is skipped — in a fresh project only the first exists. Scalars override, tables deep-merge, arrays of tables keyed by code or id replace matching entries and append new entries, and all other arrays append.
Run each entry in {workflow.activation_steps_prepend} in order.
Treat each entry in {workflow.persistent_facts} as foundational context. file: prefixes are paths or globs under
{project-root} (load contents); other entries are facts verbatim.
Resolve {user_name}, {communication_language}, {document_output_language}, {implementation_artifacts},
{project_knowledge} with a layered per-key lookup (each key comes from the first source that defines it): {project-root}/.stellar-build/bmm/config.yaml (+ config.user.yaml), then
~/.stellar-build/config.yaml (global, installer-written; in sandboxed installs it lives under the install prefix), then defaults. Never block on missing config files. If
{implementation_artifacts} is unresolved, fall back to ./investigations/ and surface the fallback before
initializing.
Greet {user_name} in {communication_language}.
Run each entry in {workflow.activation_steps_append} in order.
Acknowledge the input as a reference (record paths and IDs; don't read raw content). Path to an existing case file → Outcome 0. Otherwise → Outcome 1.
Read the case file. Surface, in order: open hypotheses (Status = Open) with their confirm/refute criteria; open
backlog (Status ≠ Done); missing-evidence rows; last Conclusion with confidence. Ask which thread to pull. New
evidence opens a new ## Follow-up: {YYYY-MM-DD} block (append #2, #3 on same-day reentry). Pause for user with the recap above; wait for direction.
Acknowledge each input shape — record location, scope, time window only; bulk reads happen in Outcome 2.
If the user arrived with a hypothesis, register it as Hypothesis #1. Find the stronghold independently; the user's hypothesis is one of the things the stronghold validates or refutes.
Find a stronghold: a Confirmed piece of evidence (error message, function name, HTTP route, config parameter, test case). Anchor here.
Initialize {case_file} before branching. The path is
{implementation_artifacts}/{workflow.case_file_subdir}/{workflow.case_file_filename} with {slug} substituted (slug
and collision rules in Overview). Create the file from {workflow.case_file_template} and fill Hand-off Brief
(rough), Case Info, Problem Statement, initial Evidence Inventory.
Evidence-light branch. When no Confirmed evidence is reachable: mark the case evidence-light in the Hand-off Brief; populate the Investigation Backlog with prioritized data-collection items; record "to make progress, I need one of: …"; pause for the user to provide evidence or authorize Outcome 2 to scan more broadly.
Otherwise present scope, stronghold, file path, proposed approach. Pause for user with the recap above; wait for direction.
Survey the scene: inventory available evidence in parallel across these independent categories: diagnostic archives;
issue tracker; version control; test results; static analysis; source code. For any category exceeding ~10K tokens,
delegate to a subagent that returns a JSON manifest (paths, sizes, time windows, key fragments cited as path:line).
Classify each Available, Partial, or Missing — Missing is itself a finding. Update Evidence Inventory and Investigation Backlog. Pause for user with the recap above; wait for direction.
Update Confirmed Findings, Deduced Conclusions, Hypothesized Paths, Backlog, Timeline. Highlight contradictions to the original premise. Pause for user with the recap above; wait for direction.
Issue these first-pass scans as parallel tool calls in one message: grep for exact error strings; glob the affected
directory for parallel implementations; git log for recent changes.
Then sequentially: read the surrounding code; follow the caller chain; watch for language and process boundary crossings (compiled→scripts, IPC, host→device, configuration flow).
Lean by case type:
Investigation stops at the diagnosis; implementation is out of scope. Update Source Code Trace (Error origin, Trigger, Condition, Related files; area model when broader). Pause for user with the recap above; wait for direction.
Update {case_file}:
Present the conclusion, then a concrete next-steps menu: trivial fix → dev-story; scope/plan adjustment →
dev-story; tracked story → create-epics-and-stories; fresh review → code-review. Recommend the
highest-value action. Mitigations and workarounds are generated only on explicit request — investigation stops at the
diagnosis. Execute {workflow.on_complete} if non-empty. Pause for user with the recap above; wait for direction.
Continue work by appending to {case_file} under a new ## Follow-up: {YYYY-MM-DD} block (#2, #3 on same-day
reentry). The investigation is complete when:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
日本語の概要は準備中です。原文の説明を表示しています。
Agentic and machine-to-machine payments on Stellar. Covers x402 (HTTP 402 paid APIs via OZ Channels facilitator, fee-sponsored clients) and MPP (Machine Payments Protocol) in both Charge mode (per-request SAC) and Channel mode (off-chain commits, high-frequency). Defaults to USDC (SEP-41 SAC) on `stellar:testnet`/`stellar:pubnet` (CAIP-2). Use when selling a paid API to AI agents, building an x402 client, or designing a payment-channel architecture for high-frequency agent traffic.
日本語の概要は準備中です。原文の説明を表示しています。
Stellar Assets (classic) + trustlines + Stellar Asset Contract (SAC) bridge to smart contracts. Covers asset issuance, distribution, authorization flags, clawback, regulated assets, trustline management, and the SAC interop layer that exposes classic assets as SEP-41 contract tokens. Use when tokenizing real-world assets, issuing stablecoins, managing trustlines, or bridging classic assets to smart contracts.
日本語の概要は準備中です。原文の説明を表示しています。
Benchmark stellar-build skills to measure quality and the lift from optimization. Use when the user says "bench my skills", "bench-skills", "benchmark skills", "did optimization help", "measure my skills", "stellar-loop bench", or wants to quantify whether /optimize-skills actually improved things. Held-out eval prompts scored by an LLM judge, reproducible with fixed seeds. Fully local.
日本語の概要は準備中です。原文の説明を表示しています。
Facilitate interactive brainstorming sessions using diverse creative techniques and ideation methods. Use when the user says help me brainstorm or help me ideate.
日本語の概要は準備中です。原文の説明を表示しています。
Technical documentation specialist and knowledge curator. Use when the user asks to talk to Bri or requests the tech writer.
日本語の概要は準備中です。原文の説明を表示しています。