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/datenoio/iterabledata/format-implementationnpx skills add datenoio/iterabledata --skill format-implementationgit clone --depth 1 https://github.com/datenoio/iterabledataWhat 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 | $0.00031 | $0.01221 |
| Opus 5 | $0.00015 | $0.00611 |
| Sonnet 5 | $0.00006 | $0.00244 |
| Haiku 4.5 | $0.00003 | $0.00122 |
Grade A, and why
format-implementation 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Format Implementation Guide
Adding New Formats
Step-by-Step Process
- Create format file:
iterable/datatypes/<format>.py - Implement BaseIterable: Inherit from
BaseIterableiniterable/base.py - Required methods:
read(),write(),read_bulk(),write_bulk(), etc. - Add detection: Update
iterable/helpers/detect.py - Create tests:
tests/test_<format>.py - Update dependencies: Add optional dependency to
pyproject.tomlif needed - Update documentation: Add format to docs
Implementation Pattern
from iterable.base import BaseIterable
class NewFormatIterable(BaseIterable):
def __init__(self, source, mode='r', **kwargs):
super().__init__(source, mode, **kwargs)
# Initialize format-specific resources
def read(self):
# Return iterator of dict objects
pass
def write(self, data):
# Write dict objects to file
pass
def read_bulk(self, size=1000):
# Bulk read for performance
pass
def write_bulk(self, data):
# Bulk write for performance
pass
Format Detection
Update iterable/helpers/detect.py:
- Add file extension detection
- Add magic number detection (for binary formats)
- Add content-based heuristics if needed
- Update
detect_file_type()function
Example:
def detect_file_type(filename, content=None):
# Check extension
if filename.endswith('.newformat'):
return 'newformat'
# Check magic numbers
if content and content.startswith(b'MAGIC'):
return 'newformat'
# ... existing detection logic
Adding New Codecs
Step-by-Step Process
- Create codec file:
iterable/codecs/<codec>codec.py - Implement codec class:
read(),write(),close()methods - Add detection: Update
iterable/helpers/detect.py - Add compression detection: Update format detection logic
- Create tests: Add to relevant test file or create new one
- Update dependencies: Add optional dependency to
pyproject.toml
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 · 199 lines · 31 tokens per session scan A 0645766472cf
format-implementation is a skill published in the GitHub repository datenoio/iterabledata (37 stars, last pushed 13d ago), licensed MIT. It adds 31 tokens to every session and 1,221 once invoked, about $0.0002 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 2026-08-30.
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