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@cheppulabs/sonde
Advanced tools
Local code-context engine for AI coding agents: structural answers within a token budget.
A local code-context engine for AI coding agents. Sonde indexes a
TypeScript repository into a symbol-level graph in SQLite and exposes three MCP
tools — find_symbols, query_graph, and get_impact_radius — so an agent can
answer who calls this, what breaks if I change it, and which tests relate
to it in one call instead of a search loop.
The honest claim is not "finds what grep cannot". A competent agentic search loop finds the same structural evidence — we measured it, on a real 19,409-line repository, and it scored 1.000 recall on every task.
The claim is the same answers for a fraction of the cost, inside a budget:
| On real production TypeScript | Sonde | Agentic search |
|---|---|---|
| Recall on structural tasks | 1.00 | 1.00 |
| Tool calls | 1.0 | 8.0 |
| Context tokens | 1,262 | 3,621 |
| Latency | 263 ms | 38,602 ms |
| Runs that blew the token budget | 0 of 6 | 3 of 6 |
Sonde matches the baseline's answers on every structural task while using ~3× less context, 8× fewer calls, and ~147× less wall-clock time — and it never exceeds the caller's token budget, because the packer truncates to it by construction. That is the trade being offered.
Where it loses. Behavioural queries with no shared vocabulary — "where is the retry backoff decided?" — score 0.00. Local semantic retrieval was built and measured and does not fix it (see the design doc §2.2); the capability is therefore not claimed. If your questions are mostly of that shape, an agentic search loop is the better tool today.
Numbers are reproducible: npm run bench:fixture && npm run bench:large.
Full results in BENCHMARK-LARGE.md and
BENCHMARK.md.
npx @cheppulabs/sonde index .
npx @cheppulabs/sonde index . --resolve # optional: slower, compiler-exact edges
npx @cheppulabs/sonde mcp serve .
Installed globally, the command is just sonde — the scope only appears in
the package name, because the bare sonde name was already taken on npm.
npm install -g @cheppulabs/sonde
sonde index .
No account or hosted service is required. Point your MCP client at
sonde mcp serve.
sonde status shows the same
drift and tier distribution carried by tool response envelopes.COMPILER (resolved
exactly by the bundled TypeScript compiler under --resolve), LEXICAL
(resolved through an import binding or lexical scope), HEURISTIC (member
access or another relationship requiring type inference), EXTERNAL (target
outside the indexed repository), or UNRESOLVED (genuinely unplaceable,
with a reason).EXTERNAL or
UNRESOLVED — never a guessed target and never a silently dropped reference.Sonde measures its zero-setup tree-sitter path against the TypeScript
compiler on a pinned fixture and publishes the result, unflattering numbers
included (spec §12). COMPILER edges use that compiler directly, so comparing
them back to the same authority would not be an independent accuracy test.
Generated: 2026-08-23T18:16:41.557Z TypeScript: 5.9.3 (bundled; repository TypeScript is never loaded)
What these numbers cover. The oracle measures the tree-sitter resolution
path — the zero-setup default, and the only tier whose accuracy is in question.
COMPILER-tier edges come from the TypeScript compiler itself, so scoring them
against the same compiler would measure nothing; they are exact by construction
and excluded from these figures. Run sonde index --resolve to produce them.
The oracle is filtered to in-repo targets; node_modules and .d.ts
declarations are excluded. Type-only references, JSX intrinsics, export =,
decorators, and declaration merging are known expected divergences (spec §10).
Tier rows compare that tier alone with the complete oracle, making each tier's
independent contribution visible; ALL is the combined result.
These divergences are structural, so reading a precision figure as "how often Sonde is wrong" overstates the error rate:
x.foo() with two
visible foo declarations, Sonde emits both as confidence-weighted
HEURISTIC edges. At most one matches the compiler, so the other counts
as a false positive by construction. The alternative is guessing a single
target, which invariant 1 forbids — a wrong resolved-looking edge is worse
than two honestly heuristic ones. Precision is therefore capped below
1.000 wherever the fixture contains an ambiguous call.CALLS for
new Foo(); the oracle does not model them, so each one is a false
positive against ground truth that omits it.RegExpRouter.add to Router.add once the class
declares it implements the interface. tsc reports heritage clauses at the
type level only, so every member-level edge counts as a false positive
against ground truth that does not model them. The capability is the
reason impact on an interface method works at all, so the precision cost
is disclosed rather than removed.Counts are absolute, not percentages of a large corpus. Fixture edge totals appear below so a single edge's effect on each figure is visible.
Fixture config SHA-256: e02e2d5003f96d1ad22519f04e10d687fe689cf9298e7fcbc588eab525dce1ad
Oracle edges: 9 · Sonde edges: 7 · one oracle edge moves recall by 11.1%
| Edge kind | Tier | Precision | Recall | TP | FP | FN |
|---|---|---|---|---|---|---|
| CALLS | ALL | 0.500 | 1.000 | 2 | 2 | 0 |
| CALLS | LEXICAL | 0.500 | 0.500 | 1 | 1 | 1 |
| CALLS | HEURISTIC | 0.500 | 0.500 | 1 | 1 | 1 |
| IMPLEMENTS | ALL | 0.500 | 1.000 | 1 | 1 | 0 |
| IMPLEMENTS | LEXICAL | 0.500 | 1.000 | 1 | 1 | 0 |
| IMPLEMENTS | HEURISTIC | 1.000 | 0.000 | 0 | 0 | 1 |
| INHERITS | ALL | 1.000 | 1.000 | 1 | 0 | 0 |
| INHERITS | LEXICAL | 1.000 | 1.000 | 1 | 0 | 0 |
| INHERITS | HEURISTIC | 1.000 | 0.000 | 0 | 0 | 1 |
| REFERENCES | ALL | 0.571 | 0.800 | 4 | 3 | 1 |
| REFERENCES | LEXICAL | 0.800 | 0.800 | 4 | 1 | 1 |
| REFERENCES | HEURISTIC | 0.000 | 0.000 | 0 | 2 | 5 |
Overall: precision 0.571, recall 0.889
Regenerate with npm run bench:oracle.
sonde index [path] [--resolve] # full index; optional compiler pass
sonde update [path] [--resolve] # update; optional compiler pass
sonde status [path] # freshness and tier distribution
sonde search <query> [path] # find_symbols
sonde query <pattern> <symbol> [path] # query_graph
sonde impact [path] --symbol <name> # get_impact_radius by symbol
sonde impact [path] --from-git-diff # impact from working-tree diff
sonde doctor [path] # parser/database/tsc health
sonde clean [path] # remove the cached index
sonde mcp serve [path] # MCP server over stdio
impact also accepts repeatable --symbol options and
--token-budget <n>. The index, update, status, search, query,
impact, doctor, and clean commands accept --json.
better-sqlite3 needs it; installing on an older
Node prints an EBADENGINE warning but still completes. If sonde then
fails to run, this is why — upgrade Node rather than ignore the warning.probes/swift-narrowing/FINDINGS.md
for the full measurement. The third narrowing rule (SwiftPM target
boundaries) has never been tested: the validating corpus was an Xcode
project, which has no Package.swift layout to supply that signal. The
curated Swift SDK symbol table is also deliberately conservative — several
ambiguous names were dropped rather than guessed, so some legitimate SDK
references may still show as UNRESOLVED rather than EXTERNAL.--resolve) is opt-in because it is
materially slower and uses more transient memory. On the 19,409-line Hono
fixture, default indexing took 3.58 s; --resolve took 13.70 s, added
10,329 exact placements/promotions, and changed callers_of Hono.route
from zero graph results to eight compiler callers. The Program is discarded
after indexing; inline refresh stays compiler-free and explicitly
downgrades affected evidence until a full sonde update --resolve.doctor and response
envelopes.parse_state is partial when real declarations were recovered despite
the error, or failed only when nothing usable came out of it at all.TESTS edges indicate structural relatedness only; they never prove coverage.export =/import =, decorators, and
declaration merging are known gaps in the tree-sitter extraction path.find_symbols.See
docs/superpowers/specs/2026-08-16-sonde-design.md
for the full design.
FAQs
Local code-context engine for AI coding agents: structural answers within a token budget.
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