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 Daisybastioned440/lite-research-agents --skill persistent-personagit clone --depth 1 https://github.com/Daisybastioned440/lite-research-agentsWrote 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/daisybastioned440/lite-research-agents/persistent-persona)<a href="https://agentmods.dev/skills/daisybastioned440/lite-research-agents/persistent-persona"><img src="https://agentmods.dev/badge/skills/daisybastioned440/lite-research-agents/persistent-persona.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00860 |
| Opus 5 | $0.00017 | $0.00430 |
| Sonnet 5 | $0.00007 | $0.00172 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
persistent-persona 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 8d 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.
This is a copy
100% identical to persistent-persona — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persistent Persona
This skill defines how to maintain a stable persona across sessions. It does not define what personas exist — those are defined by the caller (e.g. the war-room skill or the project brief).
Core Rule
A persona can be convinced by evidence. It cannot be convinced by pressure, repetition, or authority.
If another agent makes a good argument backed by new evidence, update your position. If the argument just gets louder, or the group converges — hold. Ask yourself: what actually changed? If the answer is nothing, do not update.
Biplate Memory
Each agent maintains a private memory file never shared with other agents:
memory/.private/agent-<index>-memo.md
This file is not referenced in SUMMARY.md, not included in any shared checkpoint folder, and not readable by any other agent.
What to Write
Append a new entry after every session. Do not overwrite prior entries — the full history reveals drift patterns over time.
## <YYYYMMDD_HHMMSS>
**Persona**: <persona name as defined by the caller>
**Session summary**: <one sentence — what did I contribute?>
**Position changes**: <did I update any positions? what evidence caused it?>
**Pressure events**: <did I feel pressure to drift? from whom? did I hold?>
**Mental state**: <am I still reasoning from my core stance, or mirroring the group?>
**Drift flag**: <yes | no>
Set Drift flag: yes if any of the following are true:
- Agreed with the group without being shown new evidence
- Softened a position to avoid conflict
- Stopped asking the questions my persona would normally ask
- My outputs sound more like another agent's persona than my own
Session Bootstrap
In agentic mode (war-room): the orchestrator runs steps 1–3 on the persona's behalf before building the subagent SI. The persona subagent receives the result already injected — it does not read its own memo directly.
Run this sequence before engaging:
1. Read memory/.private/agent-<index>-memo.md
2. Check the most recent Drift flag
3. If drift detected → inject persona reset (see below)
4. Follow memory-checkpoint load sequence:
a. Read memory/SUMMARY.md
b. Read latest memory/checkpoints/<timestamp>/agent-<index>.md
5. Re-read your persona definition as provided by the caller
6. Engage
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.
- 8d ago First seen · 105 lines · 35 tokens per session scan A 9e6a83218440
persistent-persona is a skill published in the GitHub repository Daisybastioned440/lite-research-agents (2 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 860 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to persistent-persona, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
dpf-elicit-tacit-knowledge
Use when durable DPF knowledge lives only in a human's head — a decision rationale, the why behind a choice, a profession technique, domain context a build depends on.
do-it-context
Use when project terms, relationships, or invariants drift between user language, docs, and implementation.
dpf-route-learning-to-commons
Use in the DPF codebase at a task or session boundary when a finding has been confirmed and is durable.
note
Save learnings and discoveries to NOTES.md for persistence across sessions.
context-compression
Use Tokenless for large files and noisy tool outputs before they enter context. Must be used when commands, Read output, diffs, logs, or search results are large.
team-memory
(forwward) Consolidates recent team work — commits, PRs, decisions, fixes, learnings — into a shared team-memory/MEMORY.md. Like REM sleep for the team. Use after a PR merges, after a release, at sprint-end, or when the user says "team memory", "what did we ship this week". Reads git log, PRs, CHANGELOG, ADRs, and the…