PPointerMallow
AI coding workspace

JSON Pointer navigation

A slash can name a path or belong inside a key. PointerMallow brings structured fixtures and pointer code into a Windows AI project conversation, where each lookup can be inspected before a change is accepted.

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A concrete starting point · JSON Pointer navigation ×
import re
def pointer_get(root, pointer):
    if not isinstance(pointer, str): raise ValueError("pointer text")
    if pointer == "": return root
    if not pointer.startswith("/"): raise ValueError("root slash")
    value = root
    for raw in pointer[1:].split("/"):
        if re.search(r"~(?![01])", raw): raise ValueError("escape")
        key = raw.replace("~1", "/").replace("~0", "~")
        if isinstance(value, dict): value = value[key]
        elif isinstance(value, list):
            if not re.fullmatch(r"0|[1-9][0-9]*", key):
                raise ValueError("array index")
            if len(key) > len(str(len(value))): raise IndexError(key)
            value = value[int(key)]
        else: raise ValueError("not a container")
    return value
✳Resolve a JSON Pointer against dictionaries and lists without editing them.
✓ ChangesReview before applying ↗
Illustrative workspace
01

Project

Test the empty root pointer and escaped keys, rejecting malformed escapes, missing members and noncanonical array indices.

02

Review before applying

Compare actual behavior with the expected result. If a check fails, investigate it before applying more changes.

03

Connection

Base URL, credentials and a reachable server.

Workflows

JSON Pointer navigation

Workflows ↗
A concrete starting point
import re
def pointer_get(root, pointer):
    if not isinstance(pointer, str): raise ValueError("pointer text")
    if pointer == "": return root
    if not pointer.startswith("/"): raise ValueError("root slash")
    value = root
    for raw in pointer[1:].split("/"):
        if re.search(r"~(?![01])", raw): raise ValueError("escape")
        key = raw.replace("~1", "/").replace("~0", "~")
        if isinstance(value, dict): value = value[key]
        elif isinstance(value, list):
            if not re.fullmatch(r"0|[1-9][0-9]*", key):
                raise ValueError("array index")
            if len(key) > len(str(len(value))): raise IndexError(key)
            value = value[int(key)]
        else: raise ValueError("not a container")
    return value
AI coding workspace

Trace a lookup from the input path to the value used

PointerMallow gives developers a Windows AI coding workspace for tracing structured-data behavior through a project. A failed lookup is easier to diagnose when the path, data shape and expected value are all present in the conversation. Begin with a small reproducible fixture and ask the model to inspect the implementation that actually consumes it.

Consider a JSON Pointer lookup as one request. Provide an object key containing a slash, an array index and a missing target, then state the intended outcome for each. Ask for a focused correction if the current code treats those paths incorrectly. The value comes from connecting the fixtures to your implementation and its callers.

Review the proposal beyond its successful result. An invalid path, a missing key and traversal through a scalar may require distinct treatment in your application. Read the changes and run the relevant tests, checking the error surfaced to the consumer as carefully as the value returned for a valid lookup.

Your model connection can use a supported OpenAI-compatible or Anthropic endpoint, with credentials as required. If you choose an abliterated AI model offered there, the provider’s restrictions still apply. Context limits and tools vary by model and server, so retain small fixtures that let you assess the reasoning and proposed code directly.

Specifying structured-data lookup behavior

How can I distinguish a malformed path from a missing value?

Provide separate fixtures and expected outcomes for both. Ask where parsing ends and traversal begins in the current code, then review how each failure reaches the caller. Collapsing them into one empty result may hide an input error.

Should a numeric object key be treated like an array index?

The containing data type matters. Include a fixture with a numeric-looking object key and a separate array fixture. Review the path-handling branch for each instead of assuming that identical text always names the same kind of location.

Why use a small fixture instead of a complete payload?

It isolates the data shape responsible for the problem and makes the expected result easier to verify. Remove unrelated fields and sensitive values while preserving the failing path, then confirm the correction against representative project data afterward.

Can model selection change the lookup contract?

The contract belongs to your application. A different model may suggest another error convention, but that does not authorize a behavior change. Review tool destinations too: a local model server does not make every connected tool local.

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PointerMallow · Updated 2026-10-25