agentleFS
MicrosoftKnown publishermicrosoft/aibast-agents-library/beta/store/json_doctor/SKILL.md

json-doctor

Skill8 starsChanged 3 months agoMITView on GitHub

Inspect, validate, diff or query a JSON/JSONL file. Infers the shape with per-field coverage, points at the exact line and column of a syntax error, compares two files structurally, and pulls values out by dotted path.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run this instead of improvising when the inputs are well-formed:

    line 76

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

JSON Doctor — understand, validate and compare JSON without opening it.

Four things you actually need when a JSON file is too big to read:

inspect   what shape is this? (inferred schema, key coverage, sample values)
validate  is it well-formed, and where exactly does it break?
diff      what changed between two of them, structurally?
query     pull a value out by dotted path, including through arrays

Works on .json and .jsonl. No network, no credentials, no dependencies.

WHY IT REPORTS COVERAGE, NOT JUST KEYS

A key that appears in 3% of records is a different fact from one that appears in 100%, and the difference is usually the bug. A schema that says {"id": "string"} hides that half the records have no id at all. So every inferred field carries how often it was actually present, and optional fields are named as optional.

WHY VALIDATION POINTS AT A LINE AND COLUMN

"Invalid JSON" is a useless error on a 40MB file. json.JSONDecodeError already knows the position; this surfaces it with the surrounding text so you can see the trailing comma rather than go hunting for it.

<!-- toaster:generated:begin -->

Parameters

The typed contract this capability answers to (JSON Schema — the deterministic layer):

{
  "type": "object",
  "properties": {
    "action": {
      "type": "string",
      "enum": [
        "inspect",
        "validate",
        "diff",
        "query"
      ],
      "description": "What to do."
    },
    "path": {
      "type": "string",
      "description": "Path to the JSON/JSONL file."
    },
    "other": {
      "type": "string",
      "description": "Second file, for action=diff."
    },
    "key": {
      "type": "string",
      "description": "Dotted path for action=query, e.g. users.0.name"
    }
  },
  "required": [
    "action",
    "path"
  ]
}
<!-- toaster:generated:end --><!-- toaster:generated:begin -->

Deterministic implementation

Run this instead of improvising when the inputs are well-formed:

def perform(self, **kwargs):
        action = kwargs.get("action")
        path = kwargs.get("path")
        if not path or not os.path.isfile(path):
            return json.dumps({"status": "error",
                               "message": f"file not found: {path}"}, indent=2)
        try:
            if action == "validate":
                try:
                    data, mode = _load(path)
                except (json.JSONDecodeError, ValueError) as e:
                    detail = {"status": "ok", "valid": False, "error": str(e)}
                    if isinstance(e, json.JSONDecodeError):
                        text = open(path, encoding="utf-8").read()
                        lo = max(0, e.pos - 60)
                        detail.update({"line": e.lineno, "column": e.colno,
                                       "context": text[lo:e.pos + 60]})
                    return json.dumps(detail, indent=2)
                n = len(data) if isinstance(data, list) else 1
                return json.dumps({"status": "ok", "valid": True, "mode": mode,
                                   "records": n,
                                   "root_type": _typename(data)}, indent=2)

            data, mode = _load(path)

            if action == "inspect":
                n = len(data) if isinstance(data, list) else 1
                return json.dumps({
                    "status": "ok", "mode": mode, "root_type": _typename(data),
                    "records": n, "bytes": os.path.getsize(path),
                    "fields": _infer(data),
                    "note": "coverage is the share of records containing the "
                            "field; anything under 100% is marked optional",
                }, indent=2)

            if action == "query":
                key = kwargs.get("key") or ""
                val, err = _walk(data, key)
                if err:
                    return json.dumps({"status": "error", "path": key,
                                       "message": err}, indent=2)
                return json.dumps({"status": "ok", "path": key,
                                   "type": _typename(val), "value": val}, indent=2)

            if action == "diff":
                other = kwargs.get("other")
                if not other or not os.path.isfile(other):
                    return json.dumps({"status": "error",
                                       "message": f"second file not found: {other}"}, indent=2)
                b, _ = _load(other)
                fa, fb = _infer(data), _infer(b)
                added = sorted(set(fb) - set(fa))
                removed = sorted(set(fa) - set(fb))
                changed = []
                for k in sorted(set(fa) & set(fb)):
                    if fa[k]["types"] != fb[k]["types"]:
                        changed.append({"field": k, "from": fa[k]["types"],
                                        "to": fb[k]["types"]})
                    elif fa[k]["coverage"] != fb[k]["coverage"]:
                        changed.append({"field": k, "coverage":
                                        f"{fa[k]['coverage']} -> {fb[k]['coverage']}"})
                return json.dumps({
                    "status": "ok",
                    "identical_shape": not (added or removed or changed),
                    "fields_added": added, "fields_removed": removed,
                    "fields_changed": changed,
                    "records": {"a": len(data) if isinstance(data, list) else 1,
                                "b": len(b) if isinstance(b, list) else 1},
                }, indent=2)

            return json.dumps({"status": "error",
                               "message": f"unknown action {action!r}",
                               "valid": ["inspect", "validate", "diff", "query"]}, indent=2)
        except Exception as e:
            return json.dumps({"status": "error",
                               "message": f"{type(e).__name__}: {e}"}, indent=2)
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.