Skills › BMAD Method › bmad-deep-recon › customize.toml
customize.toml
234 lines · skills/bmad-deep-recon/customize.toml at bd70c64
1# DO NOT EDIT -- overwritten on every update.
2#
3# Workflow customization surface for bmad-deep-recon.
4#
5# Override files (not edited here):
6# {project-root}/_bmad/custom/bmad-deep-recon.toml (team)
7# {project-root}/_bmad/custom/bmad-deep-recon.user.toml (personal)
9[workflow]
11# --- Configurable below. Overrides merge per BMad structural rules: ---
12# scalars: override wins
13# arrays (persistent_facts, activation_steps_*, *_sources, doc_standards,
14# external_*): append
15# arrays of tables keyed by `code`: matching key replaces, new keys append
17# Steps executed on activation: prepend runs before the skill's own
18# activation flow, append runs after it. Each entry is a literal instruction.
19activation_steps_prepend = []
20activation_steps_append = []
22# Standing context for framing the research — decision context only, never
23# evidence: the research firewall keeps project material out of findings.
24# Entries prefixed `file:` are paths or globs whose contents load as facts;
25# all others are literal facts. Empty by default so nothing local leaks into
26# research framing unasked.
27persistent_facts = []
29# Where research runs live and how each run folder is named. Draft, Process,
30# and Run all use the same folder shape: brief.md (drafted prompts),
31# imports/ (originals, full fidelity), digests/ (extracted claims),
32# {run_folder_pattern}.md (the canonical summary/report), .memlog.md.
33research_output_path = "{output_folder}/{active_initiative}"
34run_folder_pattern = "research-{topic_slug}"
36# Seed document for a new run.
37research_template = "assets/research.template.md"
39# --- Effort (Run mode) ------------------------------------------------------
40# A preset bundles the three effort knobs; any knob set here individually
41# pins that knob over the preset. What the user says in the request beats
42# both.
43#
44# preset subagents sources/round depth
45# quick low (2) 5 1
46# standard normal (3) 8 2
47# deep high (6) 12 3
48#
49# Grounding: orchestrator-worker research systems document 3-5 parallel
50# workers as the sweet spot (more only for genuinely wide work). Depth and
51# sources are caps, not quotas — dimensions stop early on coverage or
52# novelty exhaustion. Defaults are tuned for a fast run; buy more rigor
53# consciously, per run, in the request.
55preset = "standard"
57# "" = from preset. Values: none | low | normal | high
58# (0 / 2 / 3 / 6 parallel research assistants, ceiling 10; none also =
59# no-subagent environments, run inline sequentially).
60subagents = ""
62# 0 = from preset. Distinct sources actually read per dimension per round.
63# Ceiling 25 — beyond that a single round exceeds what hosted deep-research
64# products spend on an entire run.
65max_sources_per_round = 0
67# 0 = from preset. Rounds per dimension: initial pass + lead-following
68# follow-ups. Ceiling 5.
69max_depth = 0
71# Verification level, applied as material lands (never an end-of-run pass).
72# normal spot-check load-bearing claims only — fast, the default
73# high cross-check the pack's two-source classes; red-team major
74# conclusions
75# max cross-check every ledger claim + the red-team pass at full
76# breadth + primary-source-priority ranking
77validation = "normal"
79# Red-team stance pass — fresh-context skeptics hunting disconfirming
80# evidence for major conclusions: "off" (default), "offer" (proposed at the
81# plan gate), or "on" (always; headless honors only "on"). high/max
82# validation includes it for major conclusions regardless.
83red_team = "off"
85# Run the acquisition fan-out through the harness's deterministic
86# orchestration when it offers one (e.g. workflows): "off", "offer"
87# (proposed at the plan gate when available), or "on". Orchestrated runs are
88# faster wall-clock but spend more tokens.
89use_workflows = "offer"
91# Ordered model preference for spawned research assistants — first model the
92# harness can provide wins; [] lets the harness/skill choose (lead stays on
93# the strongest model; researchers at most one capable tier down; judgment
94# work never on the smallest tier; mechanical extraction may use a fast
95# tier).
96#
97# Example: subagent_models = ["<your-mid-tier-model-id>", "<your-fast-model-id>"]
98subagent_models = []
100# Source policy. Preferred sources are consulted first and weighted as more
101# credible; banned sources are never cited (their claims may still be leads
102# to verify elsewhere). Entries are domains or plain-text descriptions.
103# Draft mode writes both policies into drafted prompts.
104preferred_sources = []
105banned_sources = []
107# What is presented and handed off — never what exists: the report (the
108# canonical machine-readable summary/report) always lives in the workspace.
109# "auto" html briefing on interactive runs; md only on headless or
110# skill-invoked runs (the caller reads the md; render later at will)
111# "html" always render the briefing page (references/html-briefing.md)
112# "md" never render html
113# "both" render and present both
114output_format = "auto"
116# Theme for the HTML briefing: empty = the shipped neutral professional
117# theme, a `file:` path to a theme/brand spec, or inline directives
118# (e.g. "Canvas #122543, accent #B66D46, sans-serif, dark-mode aware").
119html_theme = ""
121# Default audience shaping for the synthesis — freeform, empty = balanced
122# technical/business register. Examples: "executive one-pager first, detail
123# after", "engineering team, keep vendor marketing out".
124audience = ""
126# Registry of extra research surfaces — internal knowledge bases or search
127# tools you subscribe to — consulted alongside web research in Run mode; each
128# entry names the tool and when to use it. Installed search-shaped MCP tools
129# are discovered automatically at the plan gate; an entry here adds routing
130# guidance the discovery can't infer.
131#
132# Examples:
133# external_sources = [
134# "Tavily MCP (tavily_search/tavily_extract): preferred web search + clean page extraction",
135# "Perplexity Sonar MCP (perplexity_ask): cited synthesized answers — chase its citations as the sources",
136# "xAI X Search MCP: live X/Twitter posts and threads, for user-voice and sentiment dimensions",
137# "Gartner MCP (corp:gartner_query): analyst data on enterprise software markets",
138# ]
139external_sources = []
141# Polish passes applied to the report at finalize. Entries are `skill:NAME`
142# directives, `file:` style guides, or plain-text instructions.
143doc_standards = ["skill:bmad-review lenses=structure,prose"]
145# Handoffs executed at finalize to route the report beyond local files. Each
146# entry names the tool and what to do; unavailable tools are skipped and
147# flagged.
148#
149# Examples:
150# "NotebookLM (notebooklm-mcp): create a notebook from the report plus the top sources, generate an audio overview, return the notebook URL"
151# "Confluence (corp:confluence_upload): publish the report to the RESEARCH space, return the page URL"
152external_handoffs = []
154# Executed after finalize. A string scalar is one instruction; an array is a
155# sequence. Empty = the run ends with the finalize summary.
156on_complete = ""
158# --- Codebase path ----------------------------------------------------------
159# Questions about this repository, answered from its code and git history.
160# Applies: subagents (empty means normal); subagent_models (locators and
161# verifiers take the fastest tier here, the exception to the rule above,
162# which is the list's last available entry; analyzers and historians take
163# its first); validation (normal verifies the load-bearing claims and any
164# question no analyzer took, high and max every claim, max one more call
165# edge); research_output_path; run_folder_pattern; output_format;
166# html_theme; doc_standards; external_handoffs; on_complete.
167# Does not apply: preset, max_sources_per_round, max_depth, red_team,
168# use_workflows (a workflow harness relays the ask to every researcher),
169# audience, research_template, the source lists, the research types.
171# Files one analyzer opens per question: a cap, not a quota. A question that
172# needs more ends with the next ask named in the document. Raise it where one
173# behavior spreads over many small files.
174codebase_file_budget = 15
176# Commits one historian follows per question, blaming only the cited lines: a
177# cap, not a quota. Raise it where the reasons sit far back in a long history.
178codebase_history_budget = 10
180# ---------------------------------------------------------------------------
181# Research types — subject lenses. Each type is a pack: a policy and craft
182# card (prioritized dimensions, non-obvious source craft, freshness bars,
183# two-source classes, downstream bindings) used by all three modes — it
184# shapes drafted prompts, native runs, and processed-report gap checks
185# alike. `when` guides type inference from the user's ask; an explicitly
186# requested type always wins. The decision shape (explore vs select) is
187# orthogonal — any type can end in a selection matrix.
188#
189# Keyed by `code`: an override with a matching code replaces the shipped
190# type, a new code appends. Empty `pack` disables a type.
191#
192# Example (add an org-specific type in team/user override TOML):
193# [[workflow.research_types]]
194# code = "regulatory"
195# name = "Regulatory Research"
196# when = "Compliance posture, licensing, or regulatory exposure for a product or market."
197# pack = "file:{project-root}/_bmad/custom/packs/regulatory.md"
198# ---------------------------------------------------------------------------
200[[workflow.research_types]]
201code = "market"
202name = "Market Research"
203when = "Market opportunity, customers, competition, sizing, or go-to-market for a product or business decision."
204pack = "types/market.md"
206[[workflow.research_types]]
207code = "domain"
208name = "Domain Research"
209when = "Understanding an industry, sector, or field: structure, players, rules, vocabulary, dynamics."
210pack = "types/domain.md"
212[[workflow.research_types]]
213code = "technical"
214name = "Technical Research"
215when = "A technology area's landscape, patterns, integration approaches, and implementation reality."
216pack = "types/technical.md"
218[[workflow.research_types]]
219code = "competitive"
220name = "Competitive Research"
221when = "Teardown of specific named competitors: offers, pricing, positioning, trajectory, their customers' sentiment."
222pack = "types/competitive.md"
224[[workflow.research_types]]
225code = "user-voice"
226name = "User-Voice Research"
227when = "What users of a product or category actually experience and want: reviews, communities, jobs-to-be-done."
228pack = "types/user-voice.md"
230[[workflow.research_types]]
231code = "academic-lit"
232name = "Academic Literature"
233when = "Published research: literature review, state of the art, grounding an approach in papers."
234pack = "types/academic-lit.md"