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 markmhendrickson/ateles --skill process-feedbackgit clone --depth 1 https://github.com/markmhendrickson/atelesWrote 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/markmhendrickson/ateles/process-feedback)<a href="https://agentmods.dev/skills/markmhendrickson/ateles/process-feedback"><img src="https://agentmods.dev/badge/skills/markmhendrickson/ateles/process-feedback.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.01065 |
| Opus 5 | $0.00012 | $0.00532 |
| Sonnet 5 | $0.00005 | $0.00213 |
| Haiku 4.5 | $0.00002 | $0.00106 |
Grade A, and why
process-feedback 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 4d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Process Feedback
Classify incoming product feedback before evaluating it, then score recommendations against the current release stage.
Default stage profile: Neotoma developer release.
Inputs
feedback_text(required): Raw feedback message(s), notes, screenshot transcript, or call summary.product_name(required): Product under review (for example,Neotoma).release_stage(required): Stage context (for example,developer_release,alpha,beta,ga).stage_principles(optional): Stage-specific goals, constraints, and positioning. If omitted for Neotoma developer release, use Neotoma repodocs/foundation/developer_release_principles.md.feedback_source(optional): Person/channel metadata.
Core Classification Buckets
Classify each feedback claim into one primary bucket:
-
Structural validity
- Question: Does this claim reveal that the problem is real, urgent, or inevitable?
- Typical examples: "Users cannot complete setup", "State drift causes failures", "No audit trail for mutations".
-
Addressability timing
- Question: Does this matter for users we are targeting at this stage, right now?
- Typical examples: requests from non-ICP users, scale asks before model validation, broad onboarding during narrow release.
-
Communication / legibility
- Question: Does this expose confusion in wording, naming, architecture explanation, or category framing?
- Typical examples: "Looks like another AI memory app", "I don't understand deterministic memory vs RAG".
If a claim spans multiple buckets, pick a primary bucket and list secondary buckets.
Stage-Aware Assessment Rules
Evaluate each claim with this sequence:
-
Extract atomic claims
- Break compound feedback into distinct claims.
- Preserve original wording as evidence.
-
Bucket each claim
- Assign primary bucket and optional secondary bucket(s).
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.
- 4d ago First seen · 141 lines · 24 tokens per session scan A 8f1cc5baf106
process-feedback is a skill published in the GitHub repository markmhendrickson/ateles (6 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 1,065 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 2026-09-03.
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