mistake-memory-guardrails

mistake-memory-guardrails is a skill for Claude Code from kaustubhhiware/agent-skills-fullstack-development. It costs 32 tokens per session (546 once invoked), scanned A, original, MIT.

A set of repository rules that records previous agent mistakes and checks them before and after edits to code, documentation, tests, configuration, or infrastructure.

In plain words
What is it for?
It is for reviewing mistake records, checking affected files and shared settings, verifying claims, and recording newly detected problems.
Why use it?
It helps prevent the same errors from being repeated and keeps changes aligned with existing project requirements.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: installed under .agents/ (shared by several agents).

Good fit It is for reviewing mistake records, checking affected files and shared settings, verifying claims, and recording newly detected problems.

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Install with agentmods
npx agentmods add skills/kaustubhhiware/agent-skills-fullstack-development/mistake-memory-guardrails
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.

Any agent
npx skills add kaustubhhiware/agent-skills-fullstack-development --skill mistake-memory-guardrails
Clone the repo
git clone --depth 1 https://github.com/kaustubhhiware/agent-skills-fullstack-development

Made for: Claude Code.

Wrote 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.

agentmods badge for mistake-memory-guardrails

README.md
[![agentmods](https://agentmods.dev/badge/skills/kaustubhhiware/agent-skills-fullstack-development/mistake-memory-guardrails/github.svg)](https://agentmods.dev/skills/kaustubhhiware/agent-skills-fullstack-development/mistake-memory-guardrails)
Your own site
<a href="https://agentmods.dev/skills/kaustubhhiware/agent-skills-fullstack-development/mistake-memory-guardrails"><img src="https://agentmods.dev/badge/skills/kaustubhhiware/agent-skills-fullstack-development/mistake-memory-guardrails/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.

agentmods 80×15 button for mistake-memory-guardrails

Your own site · 80×15
<a href="https://agentmods.dev/skills/kaustubhhiware/agent-skills-fullstack-development/mistake-memory-guardrails"><img src="https://agentmods.dev/badge/skills/kaustubhhiware/agent-skills-fullstack-development/mistake-memory-guardrails.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 546 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.00546
Opus 5 $0.00016 $0.00273
Sonnet 5 $0.00006 $0.00109
Haiku 4.5 $0.00003 $0.00055

Measured 9d ago against content hash a844afdef64c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

mistake-memory-guardrails 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 9d 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.

.agents/skills/mistake-memory-guardrails/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Mistake Memory Guardrails

Global guardrails for repository edit tasks.

Scope

Apply this skill to any repository edit task, including code, docs, tests, config, infra, and planning files.

Execution Order

  1. Read AGENT_MISTAKES.md. If missing, create it using the required schema.
  2. Read target files and map applicable scope_tags.
  3. Run guardrail checks before proposing or applying changes.
  4. Run a post-edit self-check against known mistake patterns before final response.
  5. Record every detected mistake occurrence.

Guardrail Checks

  1. Requirement fidelity and scope discipline:
  • Change only what the user requested.
  • Reject unrelated refactors and speculative additions.
  1. Cross-file consistency for shared facts/configs/interfaces:
  • Keep shared names, paths, status values, and contracts aligned across touched files.
  • Flag stale duplicated facts and mismatched defaults.
  1. Assertion quality:
  • Replace vague claims with measurable criteria.
  • Require explicit thresholds, formulas, or pass/fail conditions when asserting quality or correctness.
  1. Reproducibility metadata when claims depend on run conditions:
  • For benchmark/performance/behavior claims, capture model/tool version, dataset revision, seed, environment, and run conditions when relevant.
  • Separate deterministic correctness checks from environment-sensitive comparisons.
  1. Safety and regression checks:
  • Verify edits do not silently break existing behavior.
  • Call out potential regressions and missing validation coverage.

Mistake Recording Rules

  • Record every detected mistake occurrence.
  • Deduplicate by normalized pattern + scope_tags + prevention_rule.
    • Normalization: lowercase, trim whitespace, collapse repeated spaces.
  • If a deduplicated entry exists:
    • Increment occurrence_count.
    • Update last_seen.
    • Append new evidence (file:line and/or commit).
  • If no matching entry exists:
    • Append a new entry with all required fields from AGENT_MISTAKES.md.

Read the full file on GitHub · 71 lines

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.

  1. 9d ago First seen · 71 lines · 32 tokens per session scan A a844afdef64c

Subscribe to this mod's changes

mistake-memory-guardrails is a skill published in the GitHub repository kaustubhhiware/agent-skills-fullstack-development (16 stars, last pushed 3mo ago), licensed MIT. It adds 32 tokens to every session and 546 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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