A command for recording stakeholder feedback as structured project claims. Stakeholders are people who influence or are affected by the project, such as customers, managers, or compliance teams.

Use it to record constraints or feedback, identify conflicts with existing claims, and prepare unresolved issues for follow-up.

It keeps new requirements, corrections, preferences, and disagreements visible alongside earlier research and decisions.

feedback — Skill by grainulation

Install

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.

agentmods

npx agentmods add skills/grainulation/grainulator/feedback

Any agent

npx skills add grainulation/grainulator --skill feedback

Clone the repo

git clone --depth 1 https://github.com/grainulation/grainulator

Made for: Claude Code, Codex.

Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 403 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00015	$0.00403
Opus 5	$0.00008	$0.00201
Sonnet 5	$0.00003	$0.00081
Haiku 4.5	$0.00002	$0.00040

Measured yesterday against content hash e7f94003b8f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 yesterday.

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.

skills/feedback/SKILL.md · 50 lines

What it actually says

/feedback -- Record stakeholder input

The user is relaying feedback from stakeholders that should be incorporated into the sprint.

Arguments

$ARGUMENTS

Instructions

Parse the feedback: Identify what the stakeholder said. This could be:
- A new constraint ("CTO says prioritize speed over cost")
- A correction ("compliance says we need SOC2 Type II, not Type I")
- A direction change ("skip the custom build, focus on Auth0 vs Clerk")
- A new question ("what about latency in EU regions?")
Create feedback claims as f### claims:
- Type: constraint for hard requirements, feedback for opinions/preferences
- Evidence tier: stated (stakeholder said it, not independently verified)
- Tag with the stakeholder's name or role
Check for conflicts: Does this feedback contradict existing claims? If a stakeholder says "budget is $10K max" but research shows a solution at $15K, that's a conflict. Set conflicts_with on both claims.
Run wheat_compile to surface any new conflicts.

Print result:

Feedback recorded:
- <f001>: <summary>
- <f002>: <summary>

Conflicts introduced: <N>

Next steps:
  /resolve            -- resolve any new conflicts
  /research <topic>   -- investigate new questions from feedback
  /challenge <id>     -- test if feedback contradicts existing evidence

Changes

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.

yesterday First seen · 50 lines · 15 tokens per session scan A e7f94003b8f6

Subscribe to this mod's changes

feedback is a skill published in the GitHub repository grainulation/grainulator (87 stars, last pushed 4mo ago), licensed MIT. It adds 15 tokens to every session and 403 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 2026-08-30.

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