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.
npx agentmods add skills/jimmc414/claude-code-plugin-marketplace/tokenize-then-parsenpx skills add jimmc414/claude-code-plugin-marketplace --skill tokenize-then-parsegit clone --depth 1 https://github.com/jimmc414/claude-code-plugin-marketplaceWrote 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.
[](https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/tokenize-then-parse)<a href="https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/tokenize-then-parse"><img src="https://agentmods.dev/badge/skills/jimmc414/claude-code-plugin-marketplace/tokenize-then-parse.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.00639 |
| Opus 5 | $0.00014 | $0.00319 |
| Sonnet 5 | $0.00006 | $0.00128 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
tokenize-then-parse 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
tokenize-then-parse
When to Use
- Building interpreters or compilers
- Processing parenthesized expressions
- Structured text with clear token boundaries
- Multi-stage processing pipeline
When NOT to Use
- Simple fixed format (just split)
- Very complex grammar (use parser generator)
- No clear token boundaries
The Pattern
Tokenize text into a stream of tokens, then parse tokens into a structure.
def tokenize(s):
"""Convert string to list of tokens."""
return s.replace('(', ' ( ').replace(')', ' ) ').split()
def parse(tokens):
"""Parse tokens into nested structure."""
token = tokens.pop(0)
if token == '(':
result = []
while tokens[0] != ')':
result.append(parse(tokens))
tokens.pop(0) # Remove ')'
return result
else:
return atom(token)
def atom(token):
"""Convert token to appropriate type."""
try:
return int(token)
except ValueError:
try:
return float(token)
except ValueError:
return token
Example (from pytudes lis.py)
def tokenize(s):
"""Convert a string into a list of tokens."""
return s.replace('(', ' ( ').replace(')', ' ) ').split()
def read_from_tokens(tokens):
"""Read an expression from a sequence of tokens."""
if len(tokens) == 0:
raise SyntaxError('unexpected EOF')
token = tokens.pop(0)
if token == '(':
L = []
while tokens[0] != ')':
L.append(read_from_tokens(tokens))
tokens.pop(0) # Remove ')'
return L
elif token == ')':
raise SyntaxError('unexpected )')
else:
return atom(token)
def atom(token):
"""Numbers become numbers; every other token is a symbol."""
try:
return int(token)
except ValueError:
try:
return float(token)
except ValueError:
return Symbol(token)
def parse(program):
"""Read a Scheme expression from a string."""
return read_from_tokens(tokenize(program))
# Usage
parse("(+ 2 (* 3 4))")
# Returns: ['+', 2, ['*', 3, 4]]
parse("(define square (lambda (x) (* x x)))")
# Returns: ['define', 'square', ['lambda', ['x'], ['*', 'x', 'x']]]
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.
- 2d ago First seen · 104 lines · 28 tokens per session scan A 2f8a12c5b2c8
tokenize-then-parse is a skill published in the GitHub repository jimmc414/claude-code-plugin-marketplace (4 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 639 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 2026-09-04.
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