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FabledScribe/src/scribe/mcp/tools/shapes.py
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bvandeusenandClaude Fable 5 d4c7b0e48d
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feat(ledger): uses edges — consumption is its own relation, conformance keeps one snippet_id (#2870, milestone 294)
A shape can follow one convention canon AND call several helper canons; the
row's single snippet_id made the 2026-08 audit pick (hash_token won, the
service-function convention lost), and hook evidence — pulled a snippet, then
wrote code naming it — was stamped as instance when it is a uses fact.

- code_shape_uses (migration 0084): shape → snippet, basis, evidence; unique
  per pair; cascades with both ends. USE_BASES: reference | hook | agent |
  audit | import. A judgment-grade basis overwrites a mechanical one, never
  the reverse.
- classify_shapes items and classify_shapes_by_rule take uses=[snippet ids]
  (targets validated like snippet_id; all-or-nothing).
- The write-path hook writes a uses edge for every pulled canon the payload
  names (the instance stamp is unchanged); the proposer writes a uses edge
  for every canon a body names (reference_canons: kind + language family +
  stoplist, same rules as the reference basis) — the mechanical form of
  "auto-confirm own-import references" deferred from #2871.
- list_shapes(uses=N) lists the consumers of a canon; get_snippet's consumer
  map gains `uses` beside instances/variants.

Operator decision on #2870 (2026-08-21): keep one snippet_id, add uses edges.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-21 15:18:25 -04:00

315 lines
15 KiB
Python

"""Shape-ledger MCP tools — the classification write/read surface (#2789).
The accounting model (note 2786): the snippet library records CANON (small);
the ledger accounts for EVERY extracted shape (total). These tools are how
agents move shapes out of `unclassified` — the todo state — and how they read
what still needs judgment. The ledger rows themselves are fed by the coverage
refresh; these tools only ever judge what the sync has seen.
"""
from __future__ import annotations
from scribe.mcp._context import current_user_id
from scribe.services import coverage as coverage_svc
from scribe.services import shape_ledger as shape_ledger_svc
async def classify_shapes(
project_id: int, classifications: list[dict], via: str = "agent"
) -> dict:
"""Record judgments for a project's code shapes — in batch, as rows.
EVERY shape in a bound repo should end up classified (note 2786):
- `instance` of snippet N — it conforms to recorded canon (family-level
canon in another project counts; that fully accounts for the shape).
- `variant` of snippet N — a deliberate, named departure. `reason`
(the why) is REQUIRED; it is the record.
- `exempt` — judged genuinely one-off. `reason` REQUIRED.
- `canonical` of snippet N — this row IS the snippet's reference
(rarely set by hand; the coverage sync stamps these mechanically).
- `unclassified` — withdraw a judgment; the shape rejoins the todo.
Consumer maps belong HERE, not in prose: when an audit enumerates call
sites of a canonical helper, each call site's defining shape is an
`instance` row — a sentence in a verification detail cannot be sorted,
queried, or diffed.
Args:
project_id: The project whose ledger is being judged.
classifications: Objects of {path, symbol, status, kind?, snippet_id?,
reason?, reason_code?}. path+symbol name the shape exactly as
list_shapes shows it; kind ("sym"/"css") narrows when one file
defines both. snippet_id is required for canonical/instance/
variant; reason is required for variant/exempt. reason_code is
an OPTIONAL index beside the prose (one of: scoped-css,
one-off-handler, test-helper, convention-plumbing, pure-helper,
generated, script, typed-record) so the ledger can be filtered
and aggregated by kind of one-off — the prose stays the record.
uses is an OPTIONAL list of snippet ids this shape CALLS (#2870):
conformance (status + snippet_id) says what shape it is, uses
says which canonical helpers it consumes — a service function
can be an instance of the service-function convention AND use
hash_token. Consumer maps are uses edges; list_shapes(uses=N)
and get_snippet's `uses` read them.
via: Who is judging — "agent" (default), "audit" (a sweep), or
"import" (carrying maps recorded elsewhere).
All-or-nothing: a structural error, a missing snippet target, or no write
access applies NOTHING. Returns {"classified": N, "unmatched": [...]} —
unmatched names shapes no live ledger row matches (the tree may have
moved since you listed; re-run the project's coverage refresh to re-sync).
"""
uid = current_user_id()
return await shape_ledger_svc.classify_shapes(
uid, project_id, classifications, via=via
)
async def list_shapes(
project_id: int,
status: str = "",
path: str = "",
snippet_id: int = 0,
include_vanished: bool = False,
limit: int = 100,
offset: int = 0,
proposal: str = "",
flag: str = "",
compact: bool = False,
uses: int = 0,
) -> dict:
"""Read a project's shape ledger — `status="unclassified"` IS the todo.
Every extracted definition in the project's bound repos has a row here
(fed by the coverage refresh). Filters compose:
Args:
status: canonical | instance | variant | exempt | scoped | unclassified.
`scoped` (#2869) is the sync's mechanical stamp on one-offs by
construction (a Vue component's scoped <style> rules and its
<script setup> functions): accounted for, not judged, still
proposed against / grouped / flagged, and overridable by any
classify_shapes judgment. The human todo is `unclassified`.
path: exact file, or a directory — matches everything beneath it
(the coverage line's "largest" dirs go straight in here).
snippet_id: rows classified against this snippet (instance/variant
of it — conformance).
uses: rows that CALL this snippet (#2870) — the consumer map proper,
whatever shape each row is itself; edges come from judgments
(classify_shapes uses=), the write-path hook, and the proposer's
by-name reference hits.
include_vanished: include shapes no longer in the tree (history).
limit/offset: page through big ledgers (limit caps at 500).
compact: rows as `path · symbol · kind · status · signature` plus
snippet_id / by / proposal / diverges_from / recheck only when
set — no commits, shas or timestamps. THE form for an audit:
a full 500-row page fits the tool budget. The default rows carry
everything (shape_history-grade bookkeeping).
proposal: the proposer's queue (#2792) — "any", "canon" (rows the
machine thinks are an instance of a snippet: `proposal` carries
snippet_id, basis, score), "derive" (rows that repeat with NO
canon: `proposal.group` names the family), or one basis
(symbol/text/reference/signature/semantic).
flag: the divergence readout (#2793) — "divergence": shapes new
since the previous refresh in a directory where one canon
dominates the judged siblings and NOT proposed as that canon
(`diverges_from` names it: button B where button A is canon —
classify it: instance if it should use the canon, variant with
the why if deliberate); "recheck": judged instances/variants
whose body changed since judged (the judgment stands; confirm
it again with classify_shapes, or re-judge).
Returns {"shapes": [...], "total": N} — total counts every match, not
just this page. Each row's `classified_by` says who judged: agent /
audit / import are judgments; `mechanical` is the canonical stamp the
sync applies; `hook` is write-path EVIDENCE (#2791) — the session pulled
a snippet and then wrote code referencing/resembling it, so the shape
was stamped an instance with the evidence in `reason`. A hook row is
overridable by any classify_shapes call; it never overrides yours.
THE FAST PATH through a big todo is the proposer's queue: every coverage
refresh matches unclassified shapes against canon (strongest basis
first: same symbol elsewhere → textual containment → body references
the canon → signature resemblance → semantic) and attaches a
`proposal` to each row it can speak for. Review `proposal="canon"` by
snippet or directory, then confirm_shape_proposals the ones that hold —
hundreds at a time — and classify_shapes the rest (variant/exempt, or
instance of a different snippet). `proposal="derive"` lists the
derive-first candidates: a repeating shape with NO recorded canon is
never N loose classifications — consolidate onto a reference,
create_snippet it, then classify the group against it.
"""
uid = current_user_id()
rows, total = await shape_ledger_svc.list_project_shapes(
uid, project_id,
status=status, path=path, snippet_id=snippet_id,
include_vanished=include_vanished, limit=limit, offset=offset,
proposal=proposal, flag=flag, uses=uses,
)
return {
"shapes": [r.to_compact() if compact else r.to_dict() for r in rows],
"total": total,
}
async def classify_shapes_by_rule(
project_id: int,
path: str,
status: str,
pattern: str = "",
kind: str = "",
snippet_id: int = 0,
reason: str = "",
via: str = "agent",
include_judged: bool = False,
reason_code: str = "",
uses: list[int] | None = None,
) -> dict:
"""The sweep form of classify_shapes: ONE judgment applied to every
unclassified shape under a directory whose symbol matches a glob.
For the long tail an audit judges by family, not by row — "every scoped
rule under frontend/src/views is exempt: styles one element of its view",
"every `*_scheduler.py` symbol is an instance of ScheduledJob" — where
listing 900 rows and sending them back is the whole cost. The row form
stays the precise tool; reach for it when each row gets its own reason.
Args:
project_id: The project whose ledger is being judged.
path: A file, or a directory and everything beneath it. Required —
a sweep names what it judges.
status: instance | variant | exempt | unclassified (canonical is the
sync's stamp, not a sweep's).
pattern: Shell glob on the symbol (`*_rows`, `_*`, `modal-*`, `*`);
"" = every symbol under path.
kind: "sym" or "css" to narrow; "" = both.
snippet_id: Required for instance/variant — the canon judged against.
reason: Required for variant/exempt — the why, recorded on every row.
via: "agent" (default) | "audit" | "import".
reason_code: Optional catalogue code beside the reason (see
classify_shapes) — a sweep is exactly where one applies.
uses: Optional snippet ids every matched shape CALLS (#2870) — e.g.
"every *_scheduler.py symbol uses ScheduledJob".
include_judged: By default only unjudged rows are touched —
`unclassified` and the sync's mechanical `scoped` stamp — a
sweep never silently overwrites a judgment. True re-judges every
matching live row (use to re-confirm after a recheck, or to
revise a family you judged earlier).
One transaction: applies whole or not at all. Returns
{"classified": N, "sample": ["path::symbol", ...]} (first 12, sorted)
so you can see what the rule reached; N = 0 means the rule matched
nothing live and unclassified — widen the pattern or refresh coverage.
"""
uid = current_user_id()
try:
return await shape_ledger_svc.classify_shapes_where(
uid, project_id, path=path, status=status, pattern=pattern,
kind=kind, snippet_id=snippet_id or None, reason=reason or None,
via=via, include_judged=include_judged,
reason_code=reason_code or None, uses=uses or None,
)
except ValueError as exc:
return {"error": str(exc)}
async def shape_history(
project_id: int, path: str, symbol: str = "", limit: int = 200
) -> dict:
"""What was used here, when, and why — a shape's (or a directory's)
history from the ledger (#2793).
`shapes` are the current rows at `path` (a file, or a directory and
everything beneath it; `symbol` narrows to one definition) with
first/last-seen commits, vanished_at, and the standing judgment;
`events` are the state changes, oldest first: `classified` (status,
snippet_id, who, why — one per judgment, so a shape that was an instance
of #N and later a variant of #M shows both), `vanished`, `reappeared`,
`drifted` (the body moved under a judgment; see list_shapes flag=
"recheck"). Each event carries the commit the tree was read at.
Read it as a timeline: "instance of #N from <first classified at>,
re-judged variant of #M at <at> because <reason>, vanished at <commit>".
Read-only; requires read access to the project.
"""
uid = current_user_id()
return await shape_ledger_svc.shape_history(
uid, project_id, path, symbol=symbol, limit=limit
)
async def confirm_shape_proposals(
project_id: int,
snippet_id: int = 0,
path: str = "",
basis: str = "",
min_score: float = 0.0,
) -> dict:
"""Confirm the proposer's canon proposals you have reviewed, in batch.
The machine proposes, judgment classifies (#2792): each matching row —
live, unclassified, carrying a `proposal` with a snippet_id — becomes
`instance` of that snippet, classified_by="agent", reason naming the
basis and score. Narrow to what you actually looked at: at least one of
snippet_id (confirm one canon's whole queue after reading its
`list_shapes(proposal="canon", ...)` page), path (a directory you
audited), or basis (e.g. "symbol" and "reference" are near-certain;
"semantic" deserves a look first) is required — a bare confirm-all is
not a judgment. min_score trims a basis's tail.
Proposals you do NOT confirm are judged with classify_shapes (variant,
exempt, or instance of a different snippet) — any judgment retires the
proposal. Requires write access. Returns {"confirmed": N}.
"""
uid = current_user_id()
try:
return await shape_ledger_svc.confirm_proposals(
uid, project_id, snippet_id=snippet_id, path=path, basis=basis,
min_score=min_score,
)
except ValueError as exc:
return {"error": str(exc)}
async def refresh_pattern_coverage(project_id: int) -> dict:
"""Seed or refresh the project's shape ledger NOW, and return the readout.
The synchronous form of the arrival-moment background seed (#2802):
downloads the bound repos through the OWNER's forge connections, upserts
every extracted shape into the ledger (new shapes arrive `unclassified`),
re-stamps snippet reference locations as canonical, and recomputes the
accounting. Reach for it when the ledger must be current before you act —
a classification batch about to run, a coverage question asked directly —
rather than waiting on the background seed an enter_project triggers.
Takes seconds, not milliseconds (it moves repo archives). Requires write
access to the project. Errors name the fix: no forge connection → the
owner adds one (Settings → Integrations → Git Forges); no served repo →
bind_repo on a host a connection serves.
The refresh is also when the mechanical proposer runs (#2792): with the
repo bodies in hand it matches every changed unclassified shape against
canon and records proposals (see list_shapes proposal=), then regroups
the derive-first candidates. Semantic matching is capped per refresh, so
a large ledger's queue grows across refreshes rather than in one.
Returns the accounting payload — total, accounted, counts by status,
unclassified, repos, largest_gaps, `proposed` (canon proposals awaiting
confirmation), `derive_groups` (the biggest repeats-with-no-canon
families), `proposer` (what this refresh examined) — plus
`pattern_coverage`, the same one-line summary enter_project carries.
"""
uid = current_user_id()
coverage = await coverage_svc.refresh_for_caller(uid, project_id)
return {
"pattern_coverage": coverage_svc.coverage_line(coverage),
**coverage,
}
def register(mcp) -> None:
for fn in (
classify_shapes, classify_shapes_by_rule, list_shapes,
refresh_pattern_coverage, confirm_shape_proposals, shape_history,
):
mcp.tool(name=fn.__name__)(fn)