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 AnthonyAlcaraz/agentic-graph-rag-skills --skill letta-failure-modesgit clone --depth 1 https://github.com/AnthonyAlcaraz/agentic-graph-rag-skillsWrote 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/anthonyalcaraz/agentic-graph-rag-skills/letta-failure-modes)<a href="https://agentmods.dev/skills/anthonyalcaraz/agentic-graph-rag-skills/letta-failure-modes"><img src="https://agentmods.dev/badge/skills/anthonyalcaraz/agentic-graph-rag-skills/letta-failure-modes/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/anthonyalcaraz/agentic-graph-rag-skills/letta-failure-modes"><img src="https://agentmods.dev/badge/skills/anthonyalcaraz/agentic-graph-rag-skills/letta-failure-modes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00121 | $0.02033 |
| Opus 5 | $0.00060 | $0.01017 |
| Sonnet 5 | $0.00024 | $0.00407 |
| Haiku 4.5 | $0.00012 | $0.00203 |
Grade A, and why
letta-failure-modes 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 11d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Letta 8-Failure-Modes Diagnostic
Overview
The Letta Leaderboard for benchmarking agentic memory names eight distinct failure modes that tend to co-occur (Ch4):
- No-retrieval-when-available — model fails to recognize when relevant info is already in memory; issues unnecessary searches.
- Hierarchy-collapse — trivia in prime memory; critical facts archived or dropped.
- In-conversation-misses — agent misses key pieces of info even when present in the immediate context.
- Volume-degradation — retrieval accuracy degrades as data volume grows; performance drops at scale.
- Silent-overwrite — new info overwrites old facts instead of being layered; system cannot explain how or why things changed.
- Cross-reference-failure — related info isolated in separate silos; no pattern recognition.
- Temporal-blur — event timelines blur; agent loses temporal coherence.
- Threshold-collapse — works at hundreds of facts, quietly collapses at thousands.
This skill takes a snapshot of an agent's memory state (or a structural description) and reports which of these 8 are present, with evidence and recommended fixes. It runs static analysis — no agent inference loop required.
When to Use
- Pre-launch review of a new memory implementation
- Root-cause analysis when an agent in production is "forgetting" or "drifting"
- Periodic audit (weekly / monthly) on long-running agents
- Code review of a colleague's memory layer
Phrases: "audit my memory architecture", "why is my agent forgetting", "is my memory production-ready", "Letta Leaderboard", "memory diagnostic".
When NOT to Use
- Single failure mode you've already identified. If you know it's silent-overwrite, just go fix it; this skill's value is the cross-cutting audit, not the depth on one mode.
- Runtime monitor. This is a static diagnostic. Production needs metrics + alerts, not periodic full-audit invocation.
- Benchmark/eval. This does not produce a comparable accuracy number. For Letta Leaderboard scoring, run the actual benchmark suite.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 145 lines · 121 tokens per session scan A 0184b9beb03e
letta-failure-modes is a skill published in the GitHub repository AnthonyAlcaraz/agentic-graph-rag-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 121 tokens to every session and 2,033 once invoked, about $0.0006 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 2026-08-31.
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