SKILL.md

name	using-cldk
description	Use when querying a codebase through the CLDK Python SDK — addressing a callable, reading control/data flow, slicing, tracing a value across calls, or listing entrypoints, artifacts and configuration — in Python, TypeScript, JavaScript or Java, over an analysis.json or an attached Neo4j graph.

Using CLDK (schema v2 query surface)

One facade per language, two interchangeable backends behind each. Every accessor answers the same question whichever backend serves it, including when it has to refuse — a backend that cannot answer says so and says why, and never returns an empty value that reads like a real answer.

from cldk import CLDK
from cldk.analysis.commons.backend_config import Neo4jConnectionConfig

py = CLDK.python(project_path="/path/to/repo")                      # runs the analyzer in process
ts = CLDK.typescript(project_path="/path/to/repo")                  # ditto, subprocess
jv = CLDK.java(project_path="/path/to/repo",
               analysis_level="system_dependency_graph")            # levels matter, see below

graph = CLDK.java(project_path=None, backend=Neo4jConnectionConfig(  # read-only, no analyzer runs
    uri="bolt://localhost:7687", username="neo4j", password="…",
    application_name="daytrader8"))

CLDK(language="…").analysis(…) still works as a compatibility shim.

Identity

Ids are can://<app>/<lang>/<file>/<type>/<callable-signature>, application outermost. One can://<app>/ prefix scopes a whole application across every language it is written in — that is the property multi-language repositories depend on.

• Ids are opaque. Match on properties, never split on delimiters. An application named python yields can://python/python/…; anything reading segment 1 as the language is wrong.
• Externals are language-neutral: can://<app>/@external/<module>/<name>, no language segment, in every analyzer.
• Artifacts are language-neutral too: can://<app>/artifact/<path>. So are Package ids, which are purls (pkg:pypi/flask). These are the cross-language merge keys.

You rarely construct an id. Address things by name and let the SDK resolve:

jv.resolve_callable("TradeDirect.cancelOrder(java.lang.Integer, boolean)")
py.locate("addons/account/models/account_move.py", line=812)

Ambiguity raises with the candidates listed rather than guessing. There is no fuzzy matching anywhere, including in error messages — advice you are given is always followable verbatim.

Analysis levels

Accessors need the level that produces their data, and asking below it refuses rather than returning nothing.

level	what appears
symbol table	modules, types, callables, call sites
call graph	the call graph; resolution edges
program dependency graph	per-callable cfg / cdg / ddg
system dependency graph	the interprocedural overlay: param_in, param_out, summary

AnalysisLevel's own values are spelled with spaces, as above. The factories accept the underscored spelling too (analysis_level="system_dependency_graph"), so either works — but AnalysisLevel("system_dependency_graph") does not.

--emit neo4j always runs at full depth, so a graph backend has no shallow mode.

The query surface

Addressing — locate, locate_many, resolve_callable, resolve_value, get_source, describe.

Per-callable graphs — get_cfg, get_cdg, get_ddg. Paged, and the page tells you the truth about itself: complete is computed from a source that can disagree with the rows, never from the same match that produced them.

Slices and cones — slice_backward, slice_forward, backward_cone.

Call graph — reaches, callers_of, callees_of, call_paths_between.

Value flow — paths_between, flows_to_call, flows_to_argument. Each hop is labelled data, argument, return or control, so a path is evidence rather than an assertion.

Taint — taint(sources, sinks, sanitizers=()). m sources against n sinks in one traversal, and the only accessor that can say a flow does not exist: a pair in exhausted was searched to exhaustion. You supply the vocabulary — the SDK ships no framework catalogue. A sanitizer is told apart by shape: a bare str cuts a callable (a transforming sanitizer), a (name, within) pair cuts a variable (a validating guard, which never sits on the data path). Both cuts apply inside the search, so a witness is an unsanitized route.

Inventory — get_entrypoints, get_entrypoint_classes, get_entrypoint_coverage, get_external_symbols, the artifact and dependency getters, get_config_keys and the config-read accessors.

Bounds are never silent

Anything that can truncate reports that it did. depth and max_paths/max_nodes have documented defaults, and the result carries complete — a computed field on Slice and EdgePage, a plain one on FlowPaths — derived independently of the returned rows. A paged result also carries next_cursor; feed it back to continue.

s = jv.slice_backward("orderID", within=CANCEL, max_nodes=3)
s.total      # 35 — the size of the whole slice
s.complete   # False — so you know 3 is a window, not the answer

Do not paper over a bound by raising it blindly on a large graph; page instead.

Refusals mean something

Three kinds, and they are not interchangeable:

• Below the analyzer floor. A graph emitted by too old an analyzer is refused at attach with GraphSchemaMismatch naming the version found and the floor. Re-emit; there is no in-place upgrade.
• The data cannot support the question. Measured from the graph in front of you, never from a version string, so a re-emitted graph starts answering on its own with no SDK change.
• The analyzer does not emit it. Named, with the upstream issue where one exists.

An empty list is a real answer meaning "none"; a refusal means "not knowable here". Treat them differently.

Traps

1. A signature is not unique. Two types can declare the same one, and in TypeScript a declaration-merged name is several nodes. Address by the full key, or pass a scoping keyword, and let ambiguity raise.
2. flows_to_argument is coarse on Java. Every actual of a call site is fed by the statement containing it, so it answers True for any argument of a reached call. Paths are complete; per-argument precision is not there yet. The same coarseness reaches taint: a Java parameter crossing carries no variable name, so a (name, within) sanitizer cannot cut one. It under-cuts, which over-reports; it never invents a refutation.
3. taint's exhausted is void unless you check two other fields. An explicit depth empties it by rule, and complete is False voids the whole batch's absence claims — not just the pair the diagnostic names. Read unresolved first, then complete, then exhausted.
4. DDG provenance differs by language — three tiers in Python, two in Java, one in TypeScript. prov says which; do not compare tiers across languages.
5. get_source over Neo4j is the declaration, in process it is the body block. Both are documented, and the relation between them is exact — but they are not the same string.
6. A polyglot application is pushed in all languages, or none. A --emit neo4j push is destructive and the application prefix is shared, so pushing one language sweeps derived rows (notably @external ghosts) belonging to its siblings until they push again.

Both backends, one answer

Where a backend is genuinely lossy, it is documented and asserted rather than hidden — the Neo4j projection carries no column or byte offsets (they are -1, never 0), a module's text is not projected, and comment accessors have no comment nodes to read on some languages. Everything else is asserted equal between the two, per accessor, including on the miss paths.