dispatch-on-structure

dispatch-on-structure is a skill for Claude Code from jimmc414/claude-code-plugin-marketplace. It costs 25 tokens per session (707 once invoked), scanned A, original, MIT.

A programming pattern that chooses a different handler by examining the type or structure of each input.

In plain words
What is it for?
It helps build interpreters, abstract-syntax-tree walkers, pattern matchers, and processors for heterogeneous data.
Why use it?
It keeps processing logic organized when one program receives different kinds of data or expressions.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the norvig-patterns plugin — 54 skills shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jimmc414/claude-code-plugin-marketplace/dispatch-on-structure
Any agent
npx skills add jimmc414/claude-code-plugin-marketplace --skill dispatch-on-structure
Clone the repo
git clone --depth 1 https://github.com/jimmc414/claude-code-plugin-marketplace

Made for: Claude Code.

Or install norvig-patterns, the plugin that ships this one along with the rest of its 54 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for dispatch-on-structure

README.md
[![agentmods](https://agentmods.dev/badge/skills/jimmc414/claude-code-plugin-marketplace/dispatch-on-structure.svg)](https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/dispatch-on-structure)
Your own site
<a href="https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/dispatch-on-structure"><img src="https://agentmods.dev/badge/skills/jimmc414/claude-code-plugin-marketplace/dispatch-on-structure.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 707 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00025 $0.00707
Opus 5 $0.00013 $0.00353
Sonnet 5 $0.00005 $0.00141
Haiku 4.5 $0.00003 $0.00071

Measured 6d ago against content hash be7a760f46e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

dispatch-on-structure scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/norvig-patterns/skills/dispatch-on-structure/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

dispatch-on-structure

When to Use

  • Interpreters: different behavior per expression type
  • Processing heterogeneous data
  • Pattern matching (before Python 3.10 match)
  • AST walkers
  • Multi-type handlers

When NOT to Use

  • Homogeneous data (use single code path)
  • Object-oriented dispatch is clearer (use methods)
  • Simple type checking suffices

The Pattern

Check structure/type of input and dispatch to appropriate handler.

def process(x):
    """Dispatch based on structure of x."""
    if isinstance(x, int):
        return handle_int(x)
    if isinstance(x, list) and len(x) == 0:
        return handle_empty()
    if isinstance(x, list) and x[0] == 'quote':
        return handle_quote(x[1])
    if isinstance(x, list):
        return handle_list(x)
    raise TypeError(f"Unknown type: {type(x)}")

Example (from pytudes lis.py)

def eval(x, env=global_env):
    """Evaluate an expression in an environment."""

    # Dispatch on structure of x
    if isinstance(x, Symbol):           # Variable reference
        return env[x]

    elif not isinstance(x, List):       # Constant literal
        return x

    elif x[0] == 'quote':               # (quote exp)
        (_, exp) = x
        return exp

    elif x[0] == 'if':                  # (if test conseq alt)
        (_, test, conseq, alt) = x
        exp = conseq if eval(test, env) else alt
        return eval(exp, env)

    elif x[0] == 'define':              # (define var exp)
        (_, var, exp) = x
        env[var] = eval(exp, env)

    elif x[0] == 'lambda':              # (lambda (var...) body)
        (_, parms, body) = x
        return Procedure(parms, body, env)

    else:                               # (proc arg...)
        proc = eval(x[0], env)
        args = [eval(exp, env) for exp in x[1:]]
        return proc(*args)

# Differentiation dispatch (Differentiation.ipynb)
def D(y, x):
    """Differentiate y with respect to x."""
    if y == x:
        return 1
    if not isinstance(y, Expression):
        return 0
    if len(y.args) == 1:          # Unary: sin, cos, etc.
        return D_unary(y, x)
    if len(y.args) == 2:          # Binary: +, *, etc.
        return D_binary(y, x)
    raise ValueError(f"Unknown arity: {y}")

Read the full file on GitHub · 93 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 93 lines · 25 tokens per session scan A be7a760f46e1

Subscribe to this mod's changes

dispatch-on-structure is a skill published in the GitHub repository jimmc414/claude-code-plugin-marketplace (4 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 707 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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