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 skills add opengeos/geoai-skills --skill read-memoriesgit clone --depth 1 https://github.com/opengeos/geoai-skillsWrote 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/opengeos/geoai-skills/read-memories)<a href="https://agentmods.dev/skills/opengeos/geoai-skills/read-memories"><img src="https://agentmods.dev/badge/skills/opengeos/geoai-skills/read-memories/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/opengeos/geoai-skills/read-memories"><img src="https://agentmods.dev/badge/skills/opengeos/geoai-skills/read-memories.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00046 | $0.02100 |
| Opus 5 | $0.00023 | $0.01050 |
| Sonnet 5 | $0.00009 | $0.00420 |
| Haiku 4.5 | $0.00005 | $0.00210 |
Grade A, and why
read-memories 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 12d 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 — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use this to recover your own context from past sessions. Do NOT narrate the process to the user -- silently run the query, absorb the results, and continue with enriched context.
$0 is the keyword to search for.
Pass --here as an argument to scope the search to the current project only.
Pass --geo as an argument to additionally extract geospatial-specific context
(EPSG codes, bounding boxes, CRS info, spatial file paths, model names).
Step 1 -- Set the search path
ALL_PROJECTS="$HOME/.claude/projects/*/*.jsonl"
CURRENT_PROJECT="$HOME/.claude/projects/$(echo "$PWD" | sed 's|[/_]|-|g')/*.jsonl"
Use $CURRENT_PROJECT if any argument is --here, otherwise use $ALL_PROJECTS.
Store the chosen glob in SEARCH_PATH.
Check whether the --geo flag is present.
Step 2 -- Query with Python
Run the following Python script via python3 -c "...", substituting
<SEARCH_PATH> and <KEYWORD> with the resolved values. Escape any
single quotes in <KEYWORD> before embedding it.
python3 -c "
import json, glob, os
SEARCH_PATH = '<SEARCH_PATH>'
KEYWORD = '<KEYWORD>'.lower()
LIMIT = 40
files = sorted(glob.glob(os.path.expanduser(SEARCH_PATH)))
results = []
for fpath in files:
parts = fpath.split('/')
try:
proj_idx = parts.index('projects') + 1
project = parts[proj_idx] if proj_idx < len(parts) else 'unknown'
except ValueError:
project = 'unknown'
with open(fpath, 'r', errors='replace') as f:
for line in f:
try:
obj = json.loads(line)
except (json.JSONDecodeError, ValueError):
continue
msg = obj.get('message')
if not isinstance(msg, dict):
continue
role = msg.get('role')
if role not in ('user', 'assistant'):
continue
content = msg.get('content', '')
if isinstance(content, list):
text = ' '.join(
c.get('text', '')
for c in content
if isinstance(c, dict) and 'text' in c
)
elif isinstance(content, str):
text = content
else:
continue
if KEYWORD not in text.lower():
continue
ts = obj.get('timestamp', '')
snippet = text[:1500]
results.append({
'project': project,
'ts': ts[:16].replace('T', ' ') if ts else '',
'role': role,
'content': snippet,
})
if len(results) >= LIMIT:
break
if len(results) >= LIMIT:
break
print(f'Found {len(results)} results (limit {LIMIT})')
print('---')
for i, r in enumerate(results):
print(f'[{i+1}] project={r[\"project\"]} ts={r[\"ts\"]} role={r[\"role\"]}')
print(r['content'][:800])
print('---')
"
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.
- 12d ago First seen · 259 lines · 46 tokens per session scan A deecb0949889
read-memories is a skill published in the GitHub repository opengeos/geoai-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 2,100 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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