| name | lore |
| description | Channel-selectable research — pick where to search (web, youtube, your own files) and how deep, fan out a subagent per source, adversarially verify each claim, synthesize a cited answer. The run is self-contained in an arc (question + answer together); promotion to a durable knowledge doc is optional. Invoke on "наресёрчь", "research X", "/lore", "изучи тему", "build lore about X", "есть ли тула под". |
| argument-hint | <topic or research question> |
| user-invocable | true |
| disable-model-invocation | false |
/lore — grow lore (research → durable knowledge)
A research run is self-contained in its arc: the question lives in input/, the evidence
in workspace/, the answer in output/. Question and answer stay together in one place.
Promotion to a durable knowledge shelf (e.g. a lore/ doc) is optional and user-directed —
the user decides whether to lift the answer out and where it should land. By default the
answer just lives in its arc.
Tool files live in THIS skill's base directory (the dir holding this SKILL.md), regardless
of which project you invoke from: core/principles.md, core/channel-contract.md,
channels/*.md. Read them from there directly — do not go hunting one level up or resolving
symlink targets; the skill is self-contained.
Flow
1. Scope
Take the topic from $ARGUMENTS, or ask for it. Write a one-paragraph brief + explicit
sub-questions. (core/principles.md → Loop.)
2. Resolve the knobs (channels · depth · freshness)
Three knobs steer the run. Resolve each from the question at Scope — don't reflexively ask, and
don't blindly default. See core/principles.md → Knob resolution for the full model.
Per knob, classify the source of its value:
- explicit — given in
$ARGUMENTS or by the upstream caller/orchestrator → use as-is, NEVER
re-prompt. (This is the contract for agent callers — skip-if-provided.)
- inferable — the question gives a clear signal → infer a confident value.
- ambiguous — two values are equally defensible; the question doesn't settle it.
Decide ask-vs-infer by (confidence × cost-of-wrong). Cost-of-wrong, which sets how eager to
ask: channels > freshness > depth.
- channels — cost HIGH (wrong channel = wrong universe of sources). Infer ONLY on a clear
signal; else it's ambiguous. Heuristics: a file path / "my notes/PDF/book/local KB" →
files;
"in youtube / video / talk / demo" → youtube; "library/tool/docs/pricing/API/repo" or a plain
technical question → web (default); an explicit cross-medium signal ("across articles and
talks", "everything out there") → web+youtube. Note: bare "go deep / разберись глубоко" is a
depth signal, NOT a channel-width one — don't widen channels on it; if the topic fits both
web and youtube with no medium cue, channels is ambiguous (ask / headless-default web).
- depth — cost LOW (only scales effort). Almost always infer silently; default
standard.
"quick/just check/is there/yes-no/one fact" → quick; "deep/thorough/comprehensive/landscape"
→ deep; else standard. (core/principles.md → Depth.)
- freshness — cost MEDIUM. Auto-detect: "самое свежее/breaking/this week" →
bleeding;
year/"latest"/"now"/"актуальн" + fast-moving domain → fresh; "how X works"/theory/history →
evergreen; else → current. Tie-breaker: when the FORM is theory-shaped ("how X works") but
the SUBSTANCE is a fast-moving subfield (e.g. LLM agents, JS tooling), substance wins → current
(or fresh), not evergreen. (core/principles.md → Freshness.) When ≠ evergreen, channels
gate stale candidates at discover (cheap metadata BEFORE fan-out — rule 11).
Confidence test: would a reasonable person reading the question land on the same value? Yes →
infer. Two values equally defensible → ambiguous.
Interaction mode:
- interactive (a human is at the prompt): batch EVERY knob that needs the user into ONE
AskUserQuestion (multi-question), with the inferred value listed first and marked
"(Recommended)". Never fire three separate prompts. Knobs you resolved confidently are not asked.
- headless / agent-invoked (you are running as a subagent/tool, no human to ask): NEVER block.
Take the best inferred value per knob; for any still-ambiguous knob use the conservative default
(channels→
web, depth→standard, freshness→current); and SURFACE every assumption in the
run's output/ so the caller can correct and re-run. Rule of thumb: if you cannot put an
AskUserQuestion in front of a live human in this context, infer and flag — do not stall.
Always echo the resolved knobs before fan-out, with the source of each:
channels=web [inferred] · depth=standard [default] · freshness=fresh [inferred] — so the choice
is visible in both modes and the user can intervene.
Channel kinds (a channel states which via its discover section):
- search channels (
web, youtube) — the tool discovers sources itself.
- given-source channels (
files) — discover is SKIPPED; the source is in hand. If files
is chosen, get the path(s) — a file, a list, or a folder — before fanning out.
- wrapper channels (
deep-research) — delegate the fan-out to an external engine (the
built-in /deep-research workflow) and run lore's verify on top. lore's adversarial verify
(step 5) is still mandatory — that's the value the wrapped engine lacks.
3. Open the arc container (process)
arcs new-goal <topic-slug> — the run.- For each chosen channel:
arcs new-arc -g <topic-slug> <channel>.
arcs new-arc -g <topic-slug> synthesis.- Write the brief + sub-questions into the goal's / each channel arc's
input/.
4. Fan out (research)
For each channel arc, dispatch subagent(s) using that channels/<name>.md subagent-brief
core/principles.md. Count per the chosen depth (principles → Depth / Fan-out
calibration). Subagents write numbered reports → the channel arc's workspace/ (and may
return their distillate to you). The channel arc's output/ is written by YOU (the
dispatcher) after that channel's subagents return — a short distillate of the channel's
findings. Do not expect subagents to populate output/; that's the dispatcher's step, so the
close-guard finds it non-empty.
5. Verify (adversarial, fresh context)
For each channel output/, dispatch FRESH-context reviewer subagent(s). Check every
load-bearing claim against its cited source: full / partial / not-supported. Verify
intensity per depth: quick = one light pass; standard = one adversarial reviewer; deep =
≥2 independent perspectives per load-bearing claim + a completeness critic.
The "≥2 perspectives" for deep can be met two ways: (a) two dedicated fresh-context reviewers,
or (b) independent cross-channel corroboration counts as one perspective — a claim
confirmed by both web and youtube from independent sources already has a second angle, so
one dedicated adversarial reviewer on top satisfies the bar. But a load-bearing claim that
rests on a SINGLE source / single channel gets a dedicated 2nd reviewer regardless — no
cross-channel angle exists to lean on. Write verdicts into the channel arc's workspace/.
(principles → rule 8 + Depth.)
6. Synthesize
In the synthesis arc: input = the verified channel outputs. Write a cross-channel synthesis —
citations, disagreements, cross-validation — into the synthesis output/. Build only from
verified claims ("write last").
7. Offer promotion (OPTIONAL, user-directed)
The answer already lives in the synthesis arc's output/ (next to the question). Now ASK the
user whether to promote it to a durable knowledge shelf, and WHERE — e.g. a lore/<topic>.md
in this project, a central knowledge home, or nowhere (leave it in the arc). Default = leave
it in the arc; do not exile by default.
If the user promotes: write/merge the synthesis into the chosen destination with frontmatter
updated:, sources:, produced-by: (the goal + arc paths). If a doc already exists there,
MERGE (grow it, keep prior cited claims) and append a history line. A grown doc may become a
folder (README.md + sources/ + log.md). For files-channel sources cite a locus
(file:p.N) instead of a URL.
8. Close + report
arcs close -g <topic-slug> <channel> for each child + synthesis; then close the goal
(outputs are non-empty). Print the synthesis + the arc output path (where the answer lives) +
the promoted doc path if the user promoted it.
Hard rules
Obey core/principles.md → 10 hard rules throughout (no uncited claims; fail loudly on
blocked/empty fetch; verify quotes exist; primary sources; adversarial fresh-context verify).
Never finish with an empty or unclosed arc. Never invent page contents on a failed fetch.
