Borrowing it
Nothing to install: this file belongs to aget-framework/aget. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/aget-framework/aget/main/.claude/skills/aget-process-observation/SKILL.mdgit clone --depth 1 https://github.com/aget-framework/agetWrote 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/aget-framework/aget/aget-process-observation)<a href="https://agentmods.dev/skills/aget-framework/aget/aget-process-observation"><img src="https://agentmods.dev/badge/skills/aget-framework/aget/aget-process-observation/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/aget-framework/aget/aget-process-observation"><img src="https://agentmods.dev/badge/skills/aget-framework/aget/aget-process-observation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.01423 |
| Opus 5.5 | $0.00012 | $0.00569 |
| Sonnet 5.5 | $0.00006 | $0.00285 |
| Haiku 4.5 | $0.00003 | $0.00142 |
Grade A, and why
aget-process-observation 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- aget-process-observation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aget-process-observation
Classify captured observations and route actionable items to downstream skills. The missing middle step between capture and promotion in the capture pipeline.
Purpose
Observations are captured (/aget-record-observation) and can be promoted to L-docs (/aget-record-lesson) or issues (/aget-file-issue), but there is no governed step that classifies captured input, routes actionable items to downstream skills, and updates observation status. This skill fills that gap, implementing L665 (File-and-Route) for the capture pipeline: the user captures once, the system processes and routes optimally.
Evidence: L665 (File-and-Route), L671 (Classification Without Consequence), L669 (Principal Sense Amplification), L692 (Data Sovereignty). CAP-001 Gates 4-5 alignment. Principal observation (2026-03-18): "we are looking for the next investment. /aget-process-observation for example."
Input
$ARGUMENTS
Parameters:
| Parameter | Values | Default | Purpose |
|---|---|---|---|
--source |
Observation file path or unprocessed |
unprocessed |
What to process |
Examples:
/aget-process-observation— Process all unprocessed observations/aget-process-observation --source .aget/research/OBSERVATION_2026-04-10_patterns.md— Process specific observationprocess this observation— Process most recently captured observationroute this finding— Natural language trigger
Execution
Step 1: Resolve Source
| Source | Resolution |
|---|---|
unprocessed (default) |
Scan .aget/research/OBSERVATION_*.md for files with status: Captured |
| Specific path | Read the specified observation file directly |
| Most recent | Find latest .aget/research/OBSERVATION_*.md by date |
If 0 unprocessed observations found, report "No unprocessed observations." and stop.
Step 2: Read and Classify
For each observation, read its content and classify the input types present:
| Input Type | Indicators | Routing Implication |
|---|---|---|
| Screenshot evidence | Image references, visual description | Visual record — archive |
| Web research finding | URLs, citations, external sources | Source attribution — ontology or L-doc |
| Verbal observation | Pattern description, gap identification | Pattern/gap — L-doc or issue |
| Environmental context | State snapshot, configuration data | State record — session note |
| Metric or measurement | Numbers, counts, comparisons | Data point — rubric or spec enhancement |
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.
- 1mo ago First seen · 131 lines · 29 tokens per session scan A 329427027078
aget-process-observation is a skill published in the GitHub repository aget-framework/aget (12 stars, last pushed 7d ago), licensed Apache-2.0. It adds 29 tokens to every session and 1,423 once invoked, about $0.0001 per session on Opus 5.5. 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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