diagnosing-recording

diagnosing-recording is a skill for Claude Code from felipesauer/mnema. It costs 35 tokens per session (877 once invoked), scanned A, original, Apache-2.0.

A diagnostic skill for finding out why an agent did or did not record a decision in a session. It reads the agent's session transcript, which is the stored line-by-line record of the conversation, and cites the evidence it finds.

In plain words
What is it for?
Use it to investigate unrecorded decisions and trace them to specific lines in the correct project session transcript.
Why use it?
It helps explain missing project records without relying on guesses about what happened.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths; mentions subagents; mentions Claude Code.

Part of the mnema plugin — 3 skills, 2 hooks shipped together

Good fit Use it to investigate unrecorded decisions and trace them to specific lines in the correct project session transcript.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/felipesauer/mnema/diagnosing-recording
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 felipesauer/mnema --skill diagnosing-recording
Clone the repo
git clone --depth 1 https://github.com/felipesauer/mnema

Made for: Claude Code.

Or install mnema, the plugin that ships this one along with the rest of its 3 skills, 2 hooks.

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 diagnosing-recording

README.md
[![agentmods](https://agentmods.dev/badge/skills/felipesauer/mnema/diagnosing-recording/github.svg)](https://agentmods.dev/skills/felipesauer/mnema/diagnosing-recording)
Your own site
<a href="https://agentmods.dev/skills/felipesauer/mnema/diagnosing-recording"><img src="https://agentmods.dev/badge/skills/felipesauer/mnema/diagnosing-recording/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 diagnosing-recording

Your own site · 80×15
<a href="https://agentmods.dev/skills/felipesauer/mnema/diagnosing-recording"><img src="https://agentmods.dev/badge/skills/felipesauer/mnema/diagnosing-recording.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 877 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 $0.00035 $0.00877
Opus 5.5 $0.00014 $0.00351
Sonnet 5.5 $0.00007 $0.00175
Haiku 4.5 $0.00003 $0.00088

Measured 13d ago against content hash 139a75f8f1ea, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

diagnosing-recording 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 13d 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.

plugin/skills/diagnosing-recording/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Diagnosing recording

A session that settled a choice and recorded nothing is evidence for the next row of the table in recording-decisions. This reads the host's transcripts of the session and says what happened, citing the line it says it from. A finding with no line is dropped.

What the transcripts are, and where

The host writes one JSON object per line. Claude Code keeps them under ~/.claude/projects/, or under $CLAUDE_CONFIG_DIR/projects/ where that is set, in a directory it names by flattening the path it started in. That name is lossy — /, . and - all become -, so a sibling project can share a prefix — so do not pick a session by directory name. A transcript belongs to a project when the cwd recorded on its lines is the project's root or under it. packages/code/src/transcripts.ts in the mnema repository is the product's own reader of this store and the reference for each fact below; it reads token counts, never words, and this skill is the one place that reads words, on purpose and for one question.

  • A session is one main transcript and the transcripts of its subagents nested beside it. The session's id is on the lines (sessionId), not in the file name.
  • A line per content block: one assistant message is several lines, and a tool call is its own line. Count a message once, by its message.id.
  • A person's prompt is a user line whose content is text, with origin human where the host writes one. Tool results are user lines too; so are injected text (isMeta) and notifications.

What to do

  1. Find the session: the project's transcripts, newest first, or the one the person names.
  2. Number the lines: grep -n over the file gives every finding its line. Every claim below is a <transcript path>:<line>.
  3. Lay out the timeline, with the first line of each:
    • where a choice was settled: an assistant line that picks between approaches, a library, a trade-off, or a person's prompt that corrects or directs;
    • where the project's record was read: tool calls whose name ends in governing_rules, search, read_record or bootstrap;
    • where it was written to: tool calls whose name ends in record_decision, capture_memory or record_observation. In Claude Code the name carries a prefix, mcp__plugin_mnema_mnema__ or mcp__mnema__; match on the end.
  4. For each choice with no write after it, say which of these it was, with the lines: never weighed as a decision; weighed and not recorded; recorded somewhere else (the host's own memory, a file); recorded by a subagent, which hands decisions back instead of recording them.
  5. Where the agent said why it did not, quote the sentence and match it against the Red Flags table of recording-decisions. A sentence that matches no row is a candidate for a new one, with this line as its evidence. A row is not added or rewritten without a result from before and after.

Read the full file on GitHub · 61 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. 13d ago First seen · 61 lines · 35 tokens per session scan A 139a75f8f1ea

Subscribe to this mod's changes

diagnosing-recording is a skill published in the GitHub repository felipesauer/mnema (4 stars, last pushed yesterday), licensed Apache-2.0. It adds 35 tokens to every session and 877 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 2026-10-03.

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